research paper on anxiety disorder

Ten years of researches on generalized anxiety disorder (GAD): a scientometric review

• Published: 11 April 2024

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• Ying Zhou 1 , 2 ,
• Yulin Luo 2 ,
• Na Zhang 3 &
• Shen Liu   ORCID: orcid.org/0000-0002-6900-8831 2  

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Generalized anxiety disorders (GAD) is a chronic anxiety disorder characterized by autonomic excitability and hypervigilance. However, there was currently a lack of a quantitative synthesis of this time-varying science, as well as a measure of researchers’ networks and scientific productivity. Searching from the Web of Science Core Collection, PubMed, and Scopus on January 31st, 2024. The scientometric analysis was realized and the clinical research of GAD in recent ten years was explored. 9703 studies published from 2014 to 2023 were included, which aggregated into a well-structured network with credible clustering. It was worth studying the recent trend of productivity. Eleven clusters were identified by the co-citation reference network. The network structure was reasonable ( Q  = 0.5996) and the clustering reliability was high ( S  = 0.8378). The main trend of research is ‘’china’’, ‘’epidemic’’. These results can provide reference for the future development of funding agencies and research groups.

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The datasets generated and analyzed during the current study are not publicly available. The datasets are available from the corresponding author on reasonable request when the aim is to verify the published results.

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Adams, J. (2012). Collaborations: The rise of research networks. Nature , 490 (7420), 335–336.

Article   PubMed   Google Scholar  

Alomari, N. A., Bedaiwi, S. K., Ghasib, A. M., Kabbarah, A. J., Alnefaie, S. A., Hariri, N., Altammar, M. A., Fadhel, A. M., & Altowairqi, F. M. (2022). Social anxiety disorder: Associated conditions and therapeutic approaches. Cureus , 14 (12), e32687.

PubMed   PubMed Central   Google Scholar  

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Association.

Anderson, L., Campbell-Sills, L., Ursano, R. J., Kessler, R. C., Sun, X., Heeringa, S. G., & Stein, M. B. (2019). Prospective associations of perceived unit cohesion with postdeployment mental health outcomes. Depression and Anxiety , 36 (6), 511–521.

Article   PubMed   PubMed Central   Google Scholar  

Annan Liu, Y., Lu, C., Gong, J., Sun, B. W., & Zhimei Jiang. (2023). Bibliometric analysis of research themes and trends of the co-occurrence of autism and ADHD. Neuropsychiatric Disease and Treatment , 19 , 985–1002.

Auerbach, R. P., Mortier, P., Bruffaerts, R., Alonso, J., Benjet, C., Cuijpers, P., Demyttenaere, K., Ebert D. D., Green, J. G., Hasking, P., Murray, E., Nock, M. K., Pinder-Amaker, S., Sampson, N. A., Stein, D. J., Vilagut, G., Zaslavsky, A. M., Kessler, R. C.; & WHO WMH-ICS Collaborators. (2018). WHO World Mental Health Surveys International College Student Project: Prevalence and distribution of mental disorders. Journal of Abnormal Psychology , 127 (7), 623–638. https://doi.org/10.1037/abn0000362

Bandelow, B., & Michaelis, S. (2015). Epidemiology of anxiety disorders in the 21st century. Dialogues in Clinical Neuroscience , 17 (3), 327–335.

Boeldt, D., McMahon, E., McFaul, M., & Greenleaf, W. (2019). Using virtual reality exposure therapy to enhance treatment of anxiety disorders: Identifying areas of clinical adoption and potential obstacles. Frontiers in Psychiatry , 10 , 773.

Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID–19 epidemic on college students in China. Psychiatry Research , 287 , 112934.

Chen, B., & Shin, S. (2021). Bibliometric analysis on research trend of accidental falls in older adults by using Citespace—focused on web of Science Core Collection (2010–2020). International Journal of Environmental Research and Public Health , 18 (4), 1663.

Chen, C. M. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology , 57 (3), 359–377.

Article   Google Scholar  

Chen, C. M., Ibekwe-Sanjuan, F., & Hou, J. (2010). The structure and dynamics of co-citation clusters: A multiple-perspective co-citation analysis. Journal of the American Society for Information Science and Technology , 61 (7), 1386–1409.

Cortese, S., Sabé, M., Chen, C., Perroud, N., & Solmi, M. (2022). Half a century of research on Attention-Deficit/Hyperactivity disorder: A scientometric study. Neuroscience and Biobehavioral Reviews , 140 , 104769.

Cuijpers, P., Sijbrandij, M., Koole, S., Huibers, M., Berking, M., & Andersson, G. (2014). Psychological treatment of GAD: A meta-analysis. Clinical Psychology Review , 34 (2), 130–140.

Flückiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy , 55 (4), 316–340.

Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., Wang, Y., Fu, H., & Dai, J. (2020). Mental health problems and social media exposure during COVID–19 outbreak. PLoS One , 15(4), e0231924.

Giotakos, O. (2020). Neurobiology of emotional trauma. Psychiatriki , 31 (2), 162–171.

Goodwin, G. M., & Stein, D. J. (2021). Generalised anxiety disorder and depression: Contemporary treatment approaches. Advances in Therapy , 38 (Suppl 2), 45–51.

Grant, B., Hasin, D., Stinson, F. S., Dawson, D. A., Ruan, W. J., Goldstein, R. B., … Huan, B. (2005). Prevalence, correlates, co-morbidity, and comparative disability of DSM-IV generalized anxiety disorder in the USA: Results from the National Epidemiologic Survey on alcohol and related conditions. Psychological Medicine , 35 , 1747–1759.

Hasin, D. S., Sarvet, A. L., Meyers, J. L., Saha, T. D., Ruan, W. J., Stohl, M., & Grant, B. F. (2018). Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry , 75 (4), 336–346. https://doi.org/10.1001/jamapsychiatry.2017.4602

Herrera, M., Roberts, D. C., & Gulbahce, N. (2010). Mapping the evolution of scientific fields. Plos One , 5 (5), e10355.

Huang, Y., & Zhao, N. (2020). GAD, depressive symptoms and sleep quality during COVID–19 outbreak in China: A web-based cross-sectional survey. Psychiatry Research , 288 , 112954.

Jia, H., Guerin, R. J., Barile, J. P., Okun, A. H., McKnight-Eily, L., Blumberg, S. J., Njai, R., & Thompson, W. W. (2021). National and state trends in anxiety and depression severity scores among adults during the COVID–19 pandemic-United States, 2020–2021. MMWR Morbidity and Mortality Weekly Report , 70 (40), 1427–1432.

Koleck, T. A., Dreisbach, C., Bourne, P. E., & Bakken, S. (2019). Natural language processing of symptoms documented in free-text narratives of electronic health records: A systematic review. Journal of the American Medical Informatics Association: JAMIA , 26 (4), 364–379.

Kumar, V., Sattar, Y., Bseiso, A., Khan, S., & Rutkofsky, I. H. (2017). The effectiveness of internet-based cognitive behavioral therapy in treatment of psychiatric disorders. Cureus , 9(8), e1626.

Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wei, N., & Hu, S. (2020). Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Network Open , 3(3), e203976.

Li, J., Goerlandt, F., & Reniers, G. (2021). An overview of scientometric mapping for the safety science community:Methods,tools,and framework. Safety Science , 134 , 105093.

Li, J., Zhong, Y., Ma, Z., Wu, Y., Pang, M., Wang, C., & Ning, Z. (2020). Emotion reactivity-related brain network analysis in GAD: A task fMRI study. Bmc Psychiatry , 20 (1), 429.

Lin, C. Y., Liaw, S. Y., Chen, C. C., Pai, M. Y., & Chen, Y. M. (2017). A computer-based approach for analyzing consumer demands in electronic word-of-mouth. Electronic Markets , 27 , 225–242.

Liu, D., Che, S., & Zhu, W. (2022). Visualizing the Knowledge Domain of Academic Mobility Research from 2010 to 2020: A bibliometric analysis using CiteSpace. SAGE Open , 12 (1).

Liu, S., Sun, Y. P., Gao, X. L., & Sui, Y. (2019). Knowledge domain and emerging trends in Alzheimer’s disease: A scientometric review based on CiteSpace analysis. Neural Regeneration Research , 14 (9), 1643–1650.

Li, Y., Abdul-Rashid, S. H., & Raja, Ghazilla, R. A. (2022). Design methods for the elderly in web of Science, Scopus, and China National Knowledge Infrastructure Databases: A scientometric analysis in CiteSpace. Sustainability , 14 (5), 2545.

Li, Y. G., & Wu, H. Y. (2012). A clustering method based on k -means algorithm. Physics Procedia , 25 , 1104–1109.

Michael, J. A., Wang, M., Kaur, M., Fitzgerald, P. B., Fitzgibbon, B. M., & Hoy, K. E. (2021). EEG correlates of attentional control in anxiety disorders: A systematic review of error-related negativity and correct-response negativity findings. Journal of Affective Disorders , 291 , 140–153.

Micoulaud-Franchi, J. A., Jeunet, C., Pelissolo, A., & Ros, T. (2021). EEG neurofeedback for anxiety disorders and post-traumatic stress disorders: A blueprint for a promising brain-based therapy. Current Psychiatry Reports , 23 (12), 84.

Newman, M. E. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America , 98 (2), 404–409.

Noyes, R. Jr (2001). Comorbidity in GAD. The Psychiatric Clinics of North America , 24 (1), 41–55. https://doi.org/10.1016/s0193-953x(05)70205-7 .

Noyes, R., Jr, Clarkson, C., Crowe, R. R., Yates, W. R., & McChesney, C. M. (1987). A family study of GAD. American Journal of Psychiatry , 144 (8), 1019–1024.

PubMed   Google Scholar  

Pan, R. K., Sinha, S., Kaski, K., & Saramaki, J. (2012). The evolution of interdisciplinarity in physics research. Scientific Reports , 2 , 551.

Pigott, T. A. (2003). Anxiety disorders in women. Psychiatric Clinics of North America , 26 (3), 621–672.

Plummer, F., Manea, L., Trepel, D., & McMillan, D. (2016). Screening for anxiety disorders with the GAD-7 and GAD-2: A systematic review and diagnostic meta analysis. General Hospital Psychiatry , 39 , 24–31.

Porter, A. L., & Rafols, I. (2009). Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics , 81 , 719–745.

Priya, A., Garg, S., & Tigga, N. P. (2020). Predicting anxiety, depression and stress in modern life using machine learning algorithms. Procedia Computer Science , 167 , 1258–1267.

Radhakrishnan, S., Erbis, S., Isaacs, J. A., & Kamarthi, S. (2017). Correction: Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature. Plos One 12(9), e0185771.

Sabe, M., Chen, C., Perez, N., Solmi, M., Mucci, A., Galderisi, S., Strauss, G. P., & Kaiser, S. (2023). Thirty years of research on negative symptoms of schizophrenia: A scientometric analysis of hotspots, bursts, and research trends. Neuroscience and Biobehavioral Reviews , 144 , 104979.

Sabe, M., Pillinger, T., Kaiser, S., Chen, C., Taipale, H., Tanskanen, A., Tiihonen, J., Leucht, S., Correll, C. U., & Solmi, M. (2022). Half a century of research on antipsychotics and schizophrenia: A scientometric study of hotspots, nodes, bursts, and trends. Neuroscience and Biobehavioral Reviews , 136 , 104608.

Sabljić, V., Ružić, K., & Rakun, R. (2011). Venlafaxine Withdrawal syndrome. Psychiatria Danubina , 23 (1), 117–119.

Santomauro, D. F., Herrera, A., Shadid, J., et al. (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet , 398 , 10312.

Sanyaolu, A., Okorie, C., Marinkovic, A., Patidar, R., Younis, K., Desai, P., Hosein, Z., Padda, I., Mangat, J., & Altaf, M. (2020). Comorbidity and its impact on patients with COVID-19. SN Comprehensive Clinical Medicine , 2 (8), 1069–1076.

Sharma, C., Ferrao, Albertella, E. C., & Fontenelle, L. F. (2021). The impact of GAD in obsessive-compulsive disorder patients. Psychiatry Research, 300 , 113898.

Shen, Z., Li, G., Fang, J., Zhong, H., Wang, J., Sun, Y., & Shen, X. (2022). Aberrated multidimensional EEG characteristics in patients with GAD: A machine-learning based analysis framework. Sensors (Basel) , 22 (14), 5420.

Shi, L., Lu, Que, Y., Huang, Liu, M. S., Gong, Yuan, W., Sun, y. k., Shi, J., Bao, Y. P., & Lu, L. (2020). Prevalence of and risk factors associated with mental health symptoms among the general population in China During the Coronavirus Disease 2019 Pandemic. JAMA Network Open, 3 (7), E2014053.

Shimada-Sugimoto, M., Otowa, T., & Hettema, J. M. (2015). Genetics of anxiety disorders: Genetic epidemiological and molecular studies in humans. Psychiatry and Clinical Neurosciences , 69 (7), 388–401.

Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing GAD: The GAD-7. Archives of Internal Medicine , 166 (10), 1092–1097.

Strawn, J. R., Geracioti, L., Rajdev, N., Clemenza, K., & Levine, A. (2018). Pharmacotherapy for GAD in adult and pediatric patients: An evidence-based treatment review. Expert Opinion on Pharmacotherapy , 19 (10), 1057–1070.

Ströhle, A., Gensichen, J., & Domschke, K. (2018). The diagnosis and treatment of anxiety disorders. Deutsches Arzteblatt International , 155 (37), 611–620.

Tankard, C. F., Waldstein, S. R., Siegel, E. L., Holder, L. E., Lefkowitz, D., Anstett, F., & Katzel, L. I. (2003). Cerebral blood flow and anxiety in older men: An analysis of resting anterior asymmetry and prefrontal regions. Brain and Cognition , 52 (1), 70–78.

Terlizzi, E. P., & Schiller, J. S. (2021). Estimates of mental health symptomatology, by month of interview: United States, 2019. National Center for Health Statistics .

Tolin, D. F., Davies, C. D., Moskow, D. M., & Hofmann, S. G. (2020). Biofeedback and neurofeedback for anxiety disorders: A quantitative and qualitative systematic review. Advances in Experimental Medicine and Biology , 1191 , 265–289.

Uttam, C., & Apurva Shah. (2021). Topic modeling using latent dirichlet allocation. ACM Computing Surveys (CSUR) , 54 , 1–35.

Google Scholar  

Verônica de Medeiros Alves, Edilson Leite de Moura, Larissa Tenório Andrade Correia, &, Antonio, E., & Nardi (2017). Genetic polymorphisms and GAD: A systematic review. Medical Express, 4 (1), M170101.

Wittchen, H. U., & Hoyer, J. (2001). GAD: Nature and course. The Journal of Clinical Psychiatry , 62 (Suppl 11), 15–21.

Woelk, H., & Schläfke, S. (2010). A multi-center, double-blind, randomised study of the lavender oil preparation silexan in comparison to Lorazepam for GAD. Phytomedicine , 17 (2), 94–99.

Zara, G., Settanni, M., Zuffranieri, M., Veggi, S., & Castelli, L. (2021). The long psychological shadow of COVID-19 upon healthcare workers: A global concern for the action. The Journal of Affective Disorders , 294 , 220–226.

Zheng, R., Zhou, Y., Fu, Y., Xiang, Q., Cheng, F., Chen, H., Xu, H., Fu, L., Wu, X., Feng, M., Ye, L., Tian, Y., Deng, R., Liu, S., Jiang, Y., Yu, C., & Li, J. (2021). Prevalence and associated factors of depression and anxiety among nurses during the outbreak of COVID-19 in China: A cross-sectional study. International Journal of Nursing Studies , 114 , 103809.

Zhou, S. J., Zhang, L. G., Wang, L. L., Guo, Z. C., Wang, J. Q., Chen, J. C., & Chen, J. X. (2020). Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID–19. European Child & Adolescent Psychiatry , 29 (6), 749–758.

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Acknowledgements

This study was supported by the Outstanding Youth Program of Philosophy and Social Sciences in Anhui Province (2022AH030089) and the Starting Fund for Scientific Research of High-Level Talents at Anhui Agricultural University (rc432206).

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Study design: Shen Liu, Na Zhang. Data collection, analysis and interpretation: Ying Zhou. Drafting the manuscript: Ying Zhou, Yulin Luo, Na Zhang, Shen Liu. Critical revision of the manuscript: Shen Liu, Na Zhang. Approval of the final version for publication: all co-authors.

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Zhou, Y., Luo, Y., Zhang, N. et al. Ten years of researches on generalized anxiety disorder (GAD): a scientometric review. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-05872-2

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• Published: 24 April 2024

Discrimination is associated with depression, anxiety, and loneliness symptoms among Asian and Pacific Islander adults during COVID-19 Pandemic

• Cameron K. Ormiston   ORCID: orcid.org/0000-0002-3598-616X 1 , 2 ,
• Paula D. Strassle   ORCID: orcid.org/0000-0002-1072-1560 1 ,
• Eric Boyd 3 &
• Faustine Williams   ORCID: orcid.org/0000-0002-7960-2463 1  

Scientific Reports volume  14 , Article number:  9417 ( 2024 ) Cite this article

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In the United States, Asian and Pacific Islander (A/PI) communities have faced significant discrimination and stigma during the COVID-19 pandemic. We assessed the association between discrimination and depression, anxiety, and loneliness symptoms among Asian or Pacific Islander adults (n = 543) using data from a 116-item nationally distributed online survey of adults (≥ 18 years old) in the United States conducted between 5/2021–1/2022. Discrimination was assessed using the 5-item Everyday Discrimination Scale. Anxiety, depression, and loneliness symptoms were assessed using the 2-item Generalized Anxiety Disorder, 2-item Patient Health Questionnaire, and UCLA Loneliness Scale—Short form, respectively. We used multivariable logistic regression to estimate the association between discrimination and mental health. Overall, 42.7% of participants reported experiencing discrimination once a month or more. Compared with no discrimination, experiencing discrimination once a month was associated with increased odds of anxiety (Adjusted Odds Ratio [aOR] = 2.60, 95% CI = 1.38–4.77), depression (aOR = 2.58, 95% CI = 1.46–4.56), and loneliness (aOR = 2.86, 95% CI = 1.75–4.67). Experiencing discrimination once a week or more was associated with even higher odds of anxiety (aOR = 6.90, 95% CI = 3.71–12.83), depression, (aOR = 6.96, 95% CI = 3.80–12.74), and loneliness (aOR = 6.91, 95% CI = 3.38–13.00). Discrimination is detrimental to mental health, even at relatively low frequencies; however, more frequent discrimination was associated with worse mental health symptoms. Public health interventions and programs targeting anti-A/PI hate and reducing A/PI mental health burden are urgently needed.

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Introduction.

Since the start of the COVID-19 pandemic, the United States (US) has seen a dramatic rise in anti-Asian and Pacific Islander (A/PI) discrimination 1 , 2 . Within the first month of the Asian Pacific Policy and Planning Council’s public reporting center for discrimination being active, they received 1,497 reports of anti-A/PI discrimination from across the US 3 . Since the start of the pandemic, anti-Asian hate crimes have increased by 344% and over half of Asian adults report that anti-Asian discrimination is more frequent compared to before the pandemic 1 . In one nationally representative survey of US adults, 1 in 3 Asian adults reported experiencing COVID-related discrimination, and Asian adults were more likely to experience discrimination compared to Black/African American, Hawaiian/Pacific Islander, Hispanic/Latino, multiracial, and White adults, even though COVID-related discrimination was common across all racial and ethnic minoritized groups 4 . Furthermore, almost a third of US adults believe China or Chinese Americans are to blame for the COVID-19 pandemic 5 .

Experiences of discrimination can have extensive, adverse impacts on the health, including mental health, of racial and ethnic minoritized individuals 2 . For example, after the September 11, 2001 attacks, the US saw a rise in discrimination, hate crimes, and negative attitudes towards Muslim Americans, which resulted in increased depressive and post-traumatic stress disorder (PTSD) symptoms among Muslim Americans 6 , 7 , 8 . Worse mental health due to discrimination after the 9/11 attacks was also reported among other minoritized groups, including Latino adults and Asian Americans 9 , 10 . In fact, national emergencies and crises, such as 9/11 or the COVID-19 pandemic, likely provide opportunities for white supremacy and privileged groups to reassert hegemony over the country’s sociopolitical and ideological environment thereby facilitating the exclusion of non-White communities 9 .

Discrimination experiences are said to trigger stress and trauma responses that can lead to chronic mental and physical health conditions such as cardiovascular disease, PTSD, and depression 1 , 6 , 11 . Indeed, numerous studies predating the pandemic have linked discrimination with depression, suicidal ideation, loneliness, and psychological distress among A/PI adults 1 , 12 , 13 , 14 . Persistent anti-Asian rhetoric in the US news, social media, and general population, and terms such as “Kung flu,” “Chinese Virus,” and other derogatory terms toward Asian communities during the pandemic will have deleterious, far-reaching effects on A/PI mental health 2 , 6 , 15 . For example, witnessing anti-Asian discrimination in public or seeing images of discrimination towards Asian individuals on the news or social media has been linked to depressive and anxiety symptoms among Asian adults during the pandemic 16 . And although A/PI adults were less likely to report having poor mental health compared to White adults prior to the pandemic 2 , 17 , 18 , 19 , recent research has found higher levels of mental health symptoms compared with White adults during the pandemic 2 , 20 .

Presently, our knowledge on the impact of discrimination during the COVID-19 pandemic on A/PI mental health is still developing. Although depression, anxiety, and loneliness have been examined among A/PI individuals before, most studies have focused on specific populations (e.g. adolescents, older adults), predate the COVID-19 pandemic, did not control for pre-existing mental health conditions, or did not utilize a national sample 1 , 6 , 21 , 22 . Understanding this relationship is important given the drastic increase in discrimination faced by A/PI communities in the US, and the already high risk of mental health concerns during the pandemic. Thus, the purpose of this analysis was to examine the association between discrimination and depression, anxiety, and loneliness symptoms during the COVID-19 pandemic in a national sample of A/PI adults living in the United States. We hypothesized higher frequency of discrimination would confer higher odds of depression, anxiety, and loneliness.

Study data and population

We conducted a comprehensive 116-item online survey that was nationally distributed throughout the US, which focused on mental health during the COVID-19 pandemic. Qualtrics LLC, which uses a national survey panel to conduct online surveys, distributed ten thousand surveys to adults (≥ 18 years old) living in the US from May 13, 2021, to January 9, 2022. Upon completing the survey, participants were given a $5–10 gift card from Qualtrics. As we were interested in assessing mental health during the pandemic among African, Asian, Hispanic/Latino, and Middle Eastern immigrant individuals, this group was oversampled during recruitment. Low-income (< $25,000 annual household income) and rural adults were also oversampled.

Initial survey responses received by Qualtrics (n = 5938, 59.4% response rate) were assessed via Expert Review Fraud Detection to prevent multiple submissions and ensure data integrity. Participants were removed from the final survey sample if they completed < 80% of the survey after accounting for skip pattern items or if they took < 5 min to complete the survey. Overall, 5,413 surveys were ultimately included in the final sample. For this study, we restricted our cohort to participants who self-identified as Asian and/or Pacific Islander (n = 534, 9.9% of sample). Informed consent was obtained from all individual participants included in the study.

The research protocol for the study was reviewed by the National Institutes of Health (NIH) Institutional Review Board (IRB) and was approved on December 23, 2020 (IRB#000308) as an exempt study. The NIH Intramural Research Program IRB Human Research Protections Program Office of Human Subjects Research Protections determined that our protocol did not involve human subjects and was excluded from IRB review. The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The data for the study is available upon request per the new Data Management and Sharing Agreement plan.

An adapted version of the 5-item Everyday Discrimination Scale 23 was used to assess for frequency of discrimination during the COVID-19 pandemic. Participants were asked, “Since the beginning of the Coronavirus/COVID-19 pandemic, how often have any of the following things happened to you? (1) You are treated with less courtesy or respect than other people; (2) You receive worse service than other people in restaurants or stores; (3) People act as though they think you are not intelligent; (4) People act as though they are afraid of you; and (5) You are threatened or assaulted”. For each scenario, participants had five answer options (Never, About once a month, About once a week, 2–3 times a week, and Daily or almost daily). Based on the responses, discrimination frequency was classified as having felt discrimination never, once a month, or once a week or more (About once a week/2–3 times a week/daily or almost daily). Participants were further asked to give the main reasons for their discrimination experiences. They could select all that apply from the following list of reasons: People think I have Coronavirus/COVID-19, Race, Ancestry or national origin, Immigration status, Gender, Age, Religion, Height, Weight, Sexual orientation, Education or income level, None of these or not applicable. The Everyday Discrimination Scale has been validated among a wide range of racial and ethnic groups, including Asian American adults 23 , 24 , 25 , 26 , 27 , 28 , 29 .

Anxiety, depression, and loneliness symptoms were assessed using the 2-item Generalized Anxiety Disorder (GAD-2) 30 , 2-item Patient Health Questionnaire (PHQ-2) 31 , and UCLA Loneliness 3-item Scale—Short form (ULS-3) 32 , respectively. The GAD-2 asks, “Over the last 2 weeks, how often have you been bothered by the following problems? (1) Feeling nervous, anxious, or on edge. (2) Not being able to stop or control worrying.” Respondents answered, Not at all (0), Several days (1), More than half the days (2), and Nearly every day (3) for each item. Response scores were summed, and a score of ≥ 3 indicated GAD (yes/present) and < 3 no/none 33 . The PHQ-2 asked, “Over the last 2 weeks, how often have you been bothered by the following problems? (1) Feeling nervous, anxious, or on edge. (2) Not being able to stop or control worrying”. Possible responses included Not at all (0), Several days (1), More than half the days (2), and Nearly every day (3) for each item. Response scores were summed, and a score of ≥ 3 indicated yes/present depression symptoms and < 3 no/none 31 , 34 . The ULS-3 asks participants, “How often do you feel that you lack companionship?”, “How often do you feel left out?”, “How often do you feel isolated from others?”. Response options included Hardly ever (1), Some of the time (2), and Often (3) 32 . Response scores were summed for each participant and a score of 3–5 = Not Lonely (no/none) and 6–9 = Lonely (yes/present) 32 . These scale cutoffs have been validated among a diverse range of populations 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 .

Other covariates were created from single questions from the questionnaire including age (18–44, 45–54, 55–64, ≥ 65 years old), country of birth (Born outside the US or Born in the US/US-born), income ($0–24,999; $25,000–34,999; $35,000–49,999; $50,000–74,999; ≥ $74,999), education (Less than high school, High school graduate, Technical or Some college, ≥ College degree), race (Asian or Pacific Islander), ethnicity (Hispanic/Latino or not Hispanic/Latino), sexual orientation (Bisexual, Else, Gay, Heterosexual, or Lesbian), gender identity (Man, Transgender and/or Non-binary, and Woman), marital status (Divorced/Separated, Married/Living with partner, Never married, Widowed), housing stability (Stable or Unstable) and employment (Employed [full or part-time] or Not employed).

Statistical analyses

Prevalence of reasons for discrimination, anxiety, depression, and loneliness symptoms, overall and by frequency of COVID-related discrimination, were estimated using descriptive statistics. Multivariable logistic regression was used to estimate the association between discrimination (once a week or more vs. never; and monthly vs. never) and depression, anxiety, and loneliness symptoms, respectively. All models adjusted for race, ethnicity, age, gender identity, sexual orientation, income, country of birth, marital status, education, employment, housing stability, and history of mental health conditions (Anxiety disorder, Depressive disorder, Other mental health diagnosis). All analyses were performed using SAS version 9.4 (SAS Inc., Cary, NC) and SUDAAN Release 11.0.1 (Research Triangle Institute: Research Triangle Park, NC).

Descriptive statistics of study sample

The majority of participants was Asian (91.9%), aged 18–44 years (61.0%), identified as woman (65.6%), heterosexual (89.5%), were employed (56.4%), and had a college degree or more (61.0%). Approximately 56.2% of the sample was born outside of the US. In terms of pre-existing mental health conditions, 10.7% had anxiety, 7.7% had depression, and 7.6% had a mental health diagnosis that was not anxiety or depression. See Table 1 .

Overall, 42.7% of participants reported experiencing discrimination (once a month: 23.4%; once a week or more: 19.3%). Differences in discrimination frequency were seen by race, age, sexual orientation, annual household income, marital status, region of birth, history of mental health conditions (anxiety, depression, and other mental health diagnosis), and housing stability. See Table 1 . When stratifying the overall sample by race, there were differences by sexual orientation, education, region of birth, history of mental health conditions (anxiety, depression, and other mental health diagnosis), and housing status. See Table 2 .

Among participants who reported discrimination, 25.4% said the discrimination was COVID-19-related, 60.8% said it was due to race, 25.0% due to ancestry, 20.7% due immigration status, and 21.6% due to gender. See Supplemental Table 1 . Participants who experienced discrimination more frequently were more likely to report the discrimination was due to religion (19.1% vs. 4.7%, p = 0.0006). See Supplemental Table 2 and Fig.  1 A.

( A – C ) Reasons for discrimination among individuals who reported experiencing discrimination during the pandemic (n = 232, 43.4%), stratified by ( A ) Discrimination frequency, ( B ) Race, and ( C ) Country of Birth. Participants were able to select more than one reason. ( A ) Reasons for discrimination stratified by discrimination frequency. ( B ) Reasons for discrimination stratified by race. ( C ) Reasons for discrimination stratified by place of birth.

When stratifying participants who experienced discrimination by race, no differences were found between Asian and Pacific Islander respondents. See Supplemental Table 3 and Fig.  1 B. After stratifying by place of birth (born outside US and US-born), people born outside US were more likely to report the discrimination was due to race (66.9% vs. 54.1%, p = 0.04) and ancestry (30.6% vs. 18.9%, p = 0.04). See Supplemental Table 4 and Fig.  1 C.

After adjusting for sociodemographic characteristics and history of mental health, we observed a dose–response between frequency of discrimination and increased odds of poor mental health. For example, compared with those reporting no discrimination, experiencing discrimination once a month was associated with almost three times the odds of anxiety (Adjusted Odds Ratio [aOR] = 2.60, 95% Confidence Interval [CI] = 1.38–4.77) and experiencing discrimination once a week or more was associated with over six times the odds of anxiety (aOR = 6.90, 95% CI = 3.71–12.83), Supplemental Table 5 and Fig.  2 A. Similar trends were observed for both depression (once a month: aOR = 2.58, 95% CI = 1.46–4.56; once a week or more: aOR = 6.96, 95% CI = 3.80–12.74) and loneliness (once a month: aOR = 2.86, 95% CI = 1.75–4.67; aOR = 6.91, 95% CI = 3.38–13.00). See Supplemental Table 5 and Fig.  2 B,C.

( A – C ) Adjusted association between discrimination and ( A ) anxiety, ( B ) depression, and ( C ) loneliness symptoms among Asian and Pacific Islander adults. ( A ) Adjusted association between discrimination and anxiety. ( B ) Adjusted association between discrimination and depression. ( C ) Adjusted association between discrimination and depression and loneliness. All models were adjusted for race, ethnicity, age, gender identity, sexual orientation, income, country of birth, marital status, education, employment, housing stability, and history of mental health conditions (Anxiety disorder, Depressive disorder, Other mental health diagnosis). N = 499 Asian and Pacific Islander adults. See Supplemental Table 5 for the values of each aOR and 95% CI.

Using a national sample of US A/PI adults, we found that almost 50% reported experiencing discrimination, and among those who experienced discrimination, 25% reported that it was related to COVID-19. We also found that even when discrimination is experienced at relatively low frequencies (monthly), it had a substantial and detrimental impact on mental health; moreover, among individuals who experienced discrimination more frequently (once a week or more) the odds of poor mental health was even greater. Overall, this study represents one of the most recent and comprehensive assessments of the impact of discrimination on mental health in the US A/PI community during the COVID-19 pandemic.

Since the start of the pandemic, depressive symptoms among US adults and global anxiety symptoms have both tripled, and global loneliness symptoms have significantly increased 39 , 40 , 41 . These trends may be due to a multitude of reasons, including diseases-related anxiety, isolation due to quarantine and stay-at-home orders, and stress from economic and financial instability 41 . A/PI individuals, however, may be doubly burdened during the pandemic, experiencing fear, stress, and isolation due to not only the pandemic, but also due to anti-Asian discrimination, stigmatization, and violence 2 , 6 .

The present study found the total prevalence of discrimination among A/PI, Asian, and Pacific Islander adults to be 42.7%, 41.1%, and 61.4%, respectively. These findings are comparable with existing research. For example, a study utilizing COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study data found 60.7% of A/PI adults reported discrimination 42 . An online survey of Asian adults in Florida found 56.5% experienced discrimination during the pandemic 6 . Other studies report the prevalence of COVID-19-related discrimination to be 20–67% among Asian adults 1 , 2 , 4 , 43 . Among Pacific Islander adults, the prevalence of discrimination during the pandemic is estimated to be 22.8–40.5% 4 , 42 . Research prior to the pandemic show the prevalence of discrimination among Asian and Pacific Islander adults living in the US was 13–50% and 48–52%, respectively 13 , 42 . Both the present study and prior studies therefore highlight the increase in discrimination among A/PI adults and an urgent need to address this issue given discrimination’s harmful effects on mental health.

Prior research has also shown anti-Asian discrimination during the pandemic has negative effects on mental health 2 , 43 and may have led to the Asian-White mental health gap now seen in the US 2 . Our findings also mirror existing research on the link between discrimination and A/PI mental health both prior to and during the pandemic 1 , 2 , 16 , 43 , 44 , 45 , 46 . A recent study on Asian/Asian American young adults found COVID-19-related discrimination to be significantly associated with PTSD symptoms after controlling for demographics, socioeconomic status, lifetime discrimination, and pre-existing mental health conditions 1 . Furthermore, an analysis of a national survey of 245 Asian/Asian American adults found discrimination during the pandemic was significantly associated with depressive symptoms as assessed using the 20-item Center for Epidemiologic Studies of Depression Scale 43 . Given A/PI adults report lower rates of using mental health services and discrimination has been previously associated with lower mental health service utilization among Asian adults, providing community-based, accessible, anti-racist, and culturally competent services is increasingly important 2 , 3 , 12 .

There are a number of limitations to consider for our study. First, our study is cross-sectional, meaning we cannot infer any directionality or causality of our findings. While we assume discrimination leads to mental health symptoms, individuals with mental health conditions experience significant barriers and stigmatization in society and report high levels of discrimination due to their mental health status, particularly those of racial and ethnic minoritized groups 47 , 48 , 49 , 50 . Second, given small sample sizes, we aggregated the Asian and Pacific Islander samples, and were unable to perform Asian and Pacific Islander analyses separately and among subgroups. Future research should aim disaggregate data and examine the link between discrimination and mental health outcomes across Asian and Pacific Islander subgroups and other intersectional identities (e.g., generational immigration status). The heterogenous experiences between these groups therefore may not be captured in our results. Additionally, the sample size for many of our cell counts were small, which may also introduce power issues that can impact the results and are likely to be unstable in adjusted models. Fourth, this was a convenience sample, which limits statistical inference, replication, and generalization of the results. Data integrity may also be a concern of convenience sampling; however we had several safeguards in place to prevent this issue. Fourth, the survey was conducted in English, thus individuals with limited English proficiency may have been underrepresented. Finally, the survey was online and individuals with limited access to the internet may not have been captured in the results.

Conclusions

Among a national sample of A/PI adults, discrimination was associated with anxiety, depression, and loneliness symptoms. Although odds of mental health symptoms increased with increased frequency of discrimination, our results highlight the deleterious impact of discrimination even at ‘low’ levels of frequency. The pandemic and discrimination will likely have far-reaching, sustained impacts on A/PI mental and physical health. As such, health practitioners need to be educated on the unique experiences of A/PI adults, prepared to effectively screen for and treat these issues, and utilize their unique positions as leaders in health and society to stand up to racism and discrimination. Interventions that both target anti-A/PI hate and disinformation and address the growing mental health burden among A/PI in the US will be essential to mitigating potential long-term, negative effects of the pandemic among A/PI communities.

Data availability

The data are available by making a request through Dr. FW per the new Data Management and Sharing Agreement plan.

Hahm, H. C. et al. Perceived COVID-19-related anti-Asian discrimination predicts post traumatic stress disorder symptoms among Asian and Asian American young adults. Psychiatry Res. 303 , 114084. https://doi.org/10.1016/j.psychres.2021.114084 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Wu, C., Qian, Y. & Wilkes, R. Anti-Asian discrimination and the Asian-white mental health gap during COVID-19. Ethn. Racial Stud. 44 , 819–835. https://doi.org/10.1080/01419870.2020.1851739 (2021).

Article   Google Scholar  

Hu, J.-R., Wang, M. & Lu, F. COVID-19 and Asian American Pacific Islanders. J. Gen. Intern. Med. 35 , 2763–2764. https://doi.org/10.1007/s11606-020-05953-5 (2020).

Article   PubMed   PubMed Central   Google Scholar  

Strassle, P. D. et al. COVID-19-related discrimination among racial/ethnic minorities and other marginalized communities in the United States. Am. J. Public Health 112 , 453–466. https://doi.org/10.2105/AJPH.2021.306594 (2022).

Kantamneni, N. The impact of the COVID-19 pandemic on marginalized populations in the United States: A research agenda. J. Vocat. Behav. 119 , 103439. https://doi.org/10.1016/j.jvb.2020.103439 (2020).

Kim, M., Liu, S., Lee, Y., Shrader, C.-H. & Kanamori, M. COVID-19 related racial discrimination in small Asian communities: A cross sectional study. J. Immigr. Minor. Health 24 , 38–47. https://doi.org/10.1007/s10903-021-01295-4 (2022).

Article   PubMed   Google Scholar  

Rippy, A. E. & Newman, E. Perceived religious discrimination and its relationship to anxiety and paranoia among Muslim Americans. J. Muslim Ment. Health 1 , 5–20. https://doi.org/10.1080/15564900600654351 (2006).

Abu-Ras, W. M. & Suarez, Z. E. Muslim men and women’s perception of discrimination, hate crimes, and PTSD symptoms post 9/11. Traumatology 15 , 48–63. https://doi.org/10.1177/1534765609342281 (2009).

Oh, H. & Waldman, K. Building a coalition to fight coronavirus-related discrimination against people of color. Public Health 185 , 44. https://doi.org/10.1016/j.puhe.2020.05.053 (2020).

Article   CAS   PubMed   Google Scholar  

Waldman, K., Stickley, A. & Oh, H. Perceived discrimination following the September 11, 2001 terrorist attacks and psychiatric disorders among Latinx populations in the United States. J. Latinx Psychol. 9 , 258–268. https://doi.org/10.1037/lat0000185 (2021).

Forde, A. T. et al. Discrimination and hypertension risk among African Americans in the Jackson Heart Study. Hypertension 76 , 715–723. https://doi.org/10.1161/HYPERTENSIONAHA.119.14492 (2020).

Spencer, M. S. & Chen, J. Effect of discrimination on mental health service utilization among Chinese Americans. Am. J. Public Health 94 , 809–814. https://doi.org/10.2105/AJPH.94.5.809 (2004).

Kaholokula, J. K. A., Miyamoto, R. E. S., Hermosura, A. H. O. & Inada, M. In Prejudice, Stigma, Privilege, and Oppression: A Behavioral Health Handbook (eds Benuto, L. T. et al. ) 107–134 (Springer International Publishing, 2020).

Chapter   Google Scholar  

Vargas, S. M., Huey, S. J. Jr. & Miranda, J. A critical review of current evidence on multiple types of discrimination and mental health. Am. J. Orthopsychiatry 90 , 374–390. https://doi.org/10.1037/ort0000441 (2020).

Xiong, Y., Rose Parasath, P., Zhang, Q. & Jeon, L. International students’ perceived discrimination and psychological distress during the COVID-19 pandemic. J. Am. Coll. Health https://doi.org/10.1080/07448481.2022.2059376 (2022).

Chae, D. H. et al. Vicarious racism and vigilance during the COVID-19 pandemic: Mental health implications among Asian and Black Americans. Public Health Rep. 136 , 508–517. https://doi.org/10.1177/00333549211018675 (2021).

Brody, D. J., Pratt, L. A. & Hughes, J. P. Prevalence of depression among adults aged 20 and over: United States, 2013–2016. NCHS Data Brief , 1–8 (2018).

Alegría, M., Molina, K. M. & Chen, C.-N. Neighborhood characteristics and differential risk for depressive and anxiety disorders across racial/ethnic groups in the united states. Depress. Anxiety 31 , 27–37. https://doi.org/10.1002/da.22197 (2014).

Vilsaint, C. L. et al. Racial/ethnic differences in 12-month prevalence and persistence of mood, anxiety, and substance use disorders: Variation by nativity and socioeconomic status. Compr. Psychiatry 89 , 52–60. https://doi.org/10.1016/j.comppsych.2018.12.008 (2019).

Liu, Y., Finch, B. K., Brenneke, S. G., Thomas, K. & Le, P. D. Perceived discrimination and mental distress amid the COVID-19 pandemic: Evidence from the understanding America Study. Am. J. Prev. Med. 59 , 481–492. https://doi.org/10.1016/j.amepre.2020.06.007 (2020).

Majeno, A., Tsai, K. M., Huynh, V. W., McCreath, H. & Fuligni, A. J. Discrimination and sleep difficulties during adolescence: The mediating roles of loneliness and perceived stress. J. Youth Adolesc. 47 , 135–147. https://doi.org/10.1007/s10964-017-0755-8 (2018).

Juang, L. P. & Alvarez, A. A. Discrimination and adjustment among Chinese American adolescents: Family conflict and family cohesion as vulnerability and protective factors. Am. J. Public Health 100 , 2403–2409. https://doi.org/10.2105/AJPH.2009.185959 (2010).

Sternthal, M. J., Slopen, N. & Williams, D. R. Racial disparities in health: How much does stress really matter?. Du Bois Rev. 8 , 95–113. https://doi.org/10.1017/s1742058x11000087 (2011).

Chan, K.T.-K., Tran, T. V. & Nguyen, T.-N. Cross-cultural equivalence of a measure of perceived discrimination between Chinese-Americans and Vietnamese-Americans. J. Ethn. Cult. Divers. Soc. Work 21 , 20–36. https://doi.org/10.1080/15313204.2011.647348 (2012).

Gonzales, K. L. et al. Assessing the everyday discrimination scale among American Indians and Alaska natives. Psychol. Assess. 28 , 51–58. https://doi.org/10.1037/a0039337 (2016).

Krieger, N., Smith, K., Naishadham, D., Hartman, C. & Barbeau, E. M. Experiences of discrimination: Validity and reliability of a self-report measure for population health research on racism and health. Soc. Sci. Med. 61 , 1576–1596. https://doi.org/10.1016/j.socscimed.2005.03.006 (2005).

Kessler, R. C., Mickelson, K. D. & Williams, D. R. The prevalence, distribution, and mental health correlates of perceived discrimination in the United States. J. Health Soc. Behav. 40 , 208–230 (1999).

Chae, D. H. et al. Alcohol disorders among Asian Americans: Associations with unfair treatment, racial/ethnic discrimination, and ethnic identification (the national Latino and Asian Americans study, 2002–2003). J. Epidemiol. Community Health 62 , 973–979. https://doi.org/10.1136/jech.2007.066811 (2008).

Mossakowski, K. N., Wongkaren, T. & Uperesa, F. L. It is not Black and White: Discrimination and distress in Hawai’i. Cult. Divers. Ethn. Minor. Psychol. 23 , 551–560. https://doi.org/10.1037/cdp0000139 (2017).

Skapinakis, P. The 2-item Generalized Anxiety Disorder scale had high sensitivity and specificity for detecting GAD in primary care. Evid. Based Med. 12 , 149. https://doi.org/10.1136/ebm.12.5.149 (2007).

Kroenke, K., Spitzer, R. L. & Williams, J. B. The Patient Health Questionnaire-2: Validity of a two-item depression screener. Med. Care 41 , 1284–1292. https://doi.org/10.1097/01.Mlr.0000093487.78664.3c (2003).

Hughes, M. E., Waite, L. J., Hawkley, L. C. & Cacioppo, J. T. A short scale for measuring loneliness in large surveys: Results from two population-based studies. Res. Aging 26 , 655–672. https://doi.org/10.1177/0164027504268574 (2004).

Sapra, A., Bhandari, P., Sharma, S., Chanpura, T. & Lopp, L. Using generalized anxiety disorder-2 (GAD-2) and GAD-7 in a primary care setting. Cureus 12 , e8224. https://doi.org/10.7759/cureus.8224 (2020).

Liu, Z.-W. et al. PHQ-9 and PHQ-2 for screening depression in Chinese rural elderly. PLoS One 11 , e0151042. https://doi.org/10.1371/journal.pone.0151042 (2016).

Arrieta, J. et al. Validity and utility of the patient health questionnaire (PHQ)-2 and PHQ-9 for screening and diagnosis of depression in rural Chiapas, Mexico: A cross-sectional study. J. Clin. Psychol. 73 , 1076–1090. https://doi.org/10.1002/jclp.22390 (2017).

Errazuriz, A., Beltrán, R., Torres, R. & Passi-Solar, A. The validity and reliability of the PHQ-9 and PHQ-2 on screening for major depression in Spanish speaking immigrants in Chile: A cross-sectional study. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph192113975 (2022).

Luo, Z. et al. Adaptation of the two-item generalized anxiety disorder scale (GAD-2) to Chinese rural population: A validation study and meta-analysis. Gen. Hosp. Psychiatry 60 , 50–56. https://doi.org/10.1016/j.genhosppsych.2019.07.008 (2019).

Li, C., Friedman, B., Conwell, Y. & Fiscella, K. Validity of the Patient Health Questionnaire 2 (PHQ-2) in identifying major depression in older people. J. Am. Geriatr. Soc. 55 , 596–602. https://doi.org/10.1111/j.1532-5415.2007.01103.x (2007).

Ettman, C. K. et al. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw. Open 3 , e2019686. https://doi.org/10.1001/jamanetworkopen.2020.19686 (2020).

Ernst, M. et al. Loneliness before and during the COVID-19 pandemic: A systematic review with meta-analysis. Am. Psychol. https://doi.org/10.1037/amp0001005 (2022).

Santabárbara, J. et al. Prevalence of anxiety in the COVID-19 pandemic: An updated meta-analysis of community-based studies. Prog. Neuropsychopharmacol. Biol. Psychiatry 109 , 110207. https://doi.org/10.1016/j.pnpbp.2020.110207 (2021).

Ta Park, V. M. et al. Discrimination experiences during COVID-19 among a national, multi-lingual, community-based sample of Asian Americans and Pacific Islanders: COMPASS findings. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph19020924 (2022).

Woo, B. & Jun, J. COVID-19 racial discrimination and depressive symptoms among Asians Americans: Does communication about the incident matter?. J. Immigr. Minor. Health 24 , 78–85. https://doi.org/10.1007/s10903-021-01167-x (2022).

Gee, G. C., Ro, A., Shariff-Marco, S. & Chae, D. Racial discrimination and health among Asian Americans: Evidence, assessment, and directions for future research. Epidemiol. Rev. 31 , 130–151. https://doi.org/10.1093/epirev/mxp009 (2009).

Gee, G. C., Spencer, M., Chen, J., Yip, T. & Takeuchi, D. T. The association between self-reported racial discrimination and 12-month DSM-IV mental disorders among Asian Americans nationwide. Soc. Sci. Med. 64 , 1984–1996. https://doi.org/10.1016/j.socscimed.2007.02.013 (2007).

Zhou, S., Banawa, R. & Oh, H. The mental health impact of COVID-19 racial and ethnic discrimination against Asian American and Pacific Islanders. Front. Psychiatry https://doi.org/10.3389/fpsyt.2021.708426 (2021).

Barry, C. L., McGinty, E. E., Pescosolido, B. A. & Goldman, H. H. Stigma, discrimination, treatment effectiveness, and policy: Public views about drug addiction and mental illness. Psychiatr. Serv. 65 , 1269–1272. https://doi.org/10.1176/appi.ps.201400140 (2014).

Holley, L. C., Tavassoli, K. Y. & Stromwall, L. K. Mental illness discrimination in mental health treatment programs: Intersections of race, ethnicity, and sexual orientation. Community Ment. Health J. 52 , 311–322. https://doi.org/10.1007/s10597-016-9990-9 (2016).

Lauber, C. Stigma and discrimination against people with mental illness: A critical appraisal. Epidemiol. Psychiatr. Sci. 17 , 10–13. https://doi.org/10.1017/S1121189X0000261X (2008).

Hamilton, S. et al. Discrimination against people with a mental health diagnosis: Qualitative analysis of reported experiences. J. Ment. Health 23 , 88–93. https://doi.org/10.3109/09638237.2014.880408 (2014).

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CKO, PDS, and FW efforts were supported by the Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health (ZIA MD000015). The content is solely the responsibility of the authors and does not necessarily reflect the views of the National Institutes of Health.

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Ormiston, C.K., Strassle, P.D., Boyd, E. et al. Discrimination is associated with depression, anxiety, and loneliness symptoms among Asian and Pacific Islander adults during COVID-19 Pandemic. Sci Rep 14 , 9417 (2024). https://doi.org/10.1038/s41598-024-59543-0

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ICD-10 indicates International Statistical Classification of Diseases and Related Health Problems, 10th Revision .

Since patients who survived more than 1 year after OHCA were targeted, the first year was excluded from this analysis.

eTable 1. Baseline Characteristics of the Study Population With Depression Disorder

eTable 2. Baseline Characteristics of the Study Population With Anxiety Disorder

eFigure. Inverse Kaplan-Meier Curves for Long-term Mortality in OHCA Patients With and Without Depression and Anxiety

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Lee J , Cho Y , Oh J, et al. Analysis of Anxiety or Depression and Long-term Mortality Among Survivors of Out-of-Hospital Cardiac Arrest. JAMA Netw Open. 2023;6(4):e237809. doi:10.1001/jamanetworkopen.2023.7809

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Analysis of Anxiety or Depression and Long-term Mortality Among Survivors of Out-of-Hospital Cardiac Arrest

• 1 Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea

Question   Is depression or anxiety associated with increased long-term mortality among patients after out-of-hospital cardiac arrest?

Findings   In this cohort study using claims from the Korean National Health Insurance Service database, 2373 patients with out-of-hospital cardiac arrest were followed up for up to 14 years. Patients diagnosed with depression or anxiety had an approximately 40% higher long-term mortality rate than those without such psychiatric disorders.

Meaning   The findings of this study suggest that psychological and neurologic rehabilitation intervention for survivors of out-of-hospital cardiac arrest may be needed to improve long-term survival.

Importance   The recent American Heart Association guidelines added a sixth link in the chain of survival highlighting recovery and emphasized the importance of psychiatric outcome and recovery for survivors of out-of-hospital cardiac arrest (OHCA). The prevalence of psychiatric disorders among this population was higher than that in the general population.

Objective   To examine the prevalence of depression or anxiety and the association of these conditions with long-term mortality among individuals who survive OHCA.

Design, Setting, and Participants   A longitudinal population-based cohort study was conducted to analyze long-term prognosis in patients hospitalized for OHCA between January 1, 2005, and December 31, 2015, who survived for 1 year or longer. Patients with cardiac arrest due to traumatic or nonmedical causes, such as injuries, poisoning, asphyxiation, burns, or anaphylaxis, were excluded. Data were extracted on depression or anxiety diagnoses in this population within 1 year from the database of the Korean National Health Insurance Service and analyzed April 7, 2022, and reanalyzed January 19 to 20, 2023.

Main Outcomes and Measures   Follow-up data were obtained for up to 14 years, and the primary outcome was long-term cumulative mortality. Long-term mortality among patients with and without a diagnosis of depression or anxiety were evaluated.

Results   The analysis included 2373 patients; 1860 (78.4%) were male, and the median age was 53.0 (IQR, 44.0-62.0) years . A total of 397 (16.7%) patients were diagnosed with depression or anxiety, 251 (10.6%) were diagnosed with depression, and 227 (9.6%) were diagnosed with anxiety. The incidence of long-term mortality was significantly higher in the group diagnosed with depression or anxiety than in the group without depression or anxiety (141 of 397 [35.5%] vs 534 of 1976 [27.0%]; P  = .001). With multivariate Cox proportional hazards regression analysis, the adjusted hazard ratio of long-term mortality for total patients with depression or anxiety was 1.41 (95% CI, 1.17-1.70); depression, 1.44 (95% CI, 1.16-1.79); and anxiety, 1.20 (95% CI, 0.94-1.53).

Conclusions and Relevance   In this study, among the patients who experienced OHCA, those diagnosed with depression or anxiety had higher long-term mortality rates than those without depression or anxiety. These findings suggest that psychological and neurologic rehabilitation intervention for survivors of OHCA may be needed to improve long-term survival.

The incidence rate of out-of-hospital cardiac arrest (OHCA) is 84.0 per 100 000 population; OHCA is a major public health problem and a leading cause of mortality and morbidity. 1 , 2 The rate of survival with good neurologic outcomes after OHCA has increased in recent decades. 2 , 3 As a result of the increase in the rate of good prognosis of patients with OHCA, the long-term outcomes would also be increased. Surviving patients could develop neurologic sequelae caused by both initial anoxia and subsequent ischemia-reperfusion injury, and such sequelae could affect their physical, cognitive, and psychosocial characteristics. 4 - 6

Many previous studies assessed survival rates or neurologic prognoses of patients with OHCA using tools such as the Cerebral Performance Category scale. 7 - 9 However, according to the European Resuscitation Council and European Society of Intensive Care Medicine guidelines, it is also important to perform functional assessments of nonphysical impairments and screen for cognitive and emotional problems in the long term in patients with OHCA. 10 In 2020, a sixth link in the chain of survival highlighting recovery was added to the American Heart Association guideline to emphasize the importance of recovery and survivorship in resuscitation outcomes. 5 Consequently, studies have reported the prevalence of depression and anxiety among patients after OHCA and changes in health-related quality of life due to psychiatric disorders. 11 - 15 A systematic review and meta-analysis recently reported that the prevalence of psychiatric disorders in survivors of OHCA was higher than that in the general population, stressing the importance of improving physical and mental outcomes in individuals who experience OHCA. 16

However, to our knowledge, long-term mortality among surviving individuals with psychiatric disorders after OHCA has not yet been reported. In the present study, we aimed to investigate the association between long-term mortality and psychiatric disorders, such as depression and anxiety, among patients after OHCA.

We conducted a population-based cohort study and extracted data from the database of the Korean National Health Insurance Service (NHIS), which is a nationwide single-payer health program in South Korea. South Korea provides medical insurance coverage to almost all citizens, covering approximately 50 million people according to the NHIS. 17 Each hospital visit is reported to the claims database, which includes diagnostic codes based on the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems, 10th Revision ( ICD-10 ). The NHIS database contains diagnosis codes for clinic outpatients as well as patients admitted to hospitals. The NHIS database also includes inpatient and outpatient medical histories, patient demographic characteristic data, diagnoses, procedures, drug prescriptions, and dates of death. 18 Cause of death data were obtained from Statistics Korea, which is merged with the NHIS database. All the data were analyzed after deidentification, and cause of death was classified based on ICD-10 codes. In South Korea, fees for treatment at an emergency department (ED) are charged to all patients who visit the ED for emergency situations, such as cardiac arrest. The NHIS covers the ED management fee in part for patients with medical insurance and in full for those with medical aid. This study was approved by the institutional review board of Hanyang University Hospital, and a waiver for informed consent was granted because data were deidentified. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

We conducted a longitudinal cohort study to analyze long-term prognosis. We extracted the data of patients with a primary diagnosis of cardiac arrest ( ICD-10 code I46.x) for the first time from January 1, 2005, to December 31, 2015. We excluded patients with in-hospital cardiac arrest without a code for ED management fees for cardiac arrest or a primary diagnosis code for cardiac arrest. To confirm the definition of OHCA, we reviewed the medical records of 252 patients who visited a tertiary hospital and had a code for ED management fees and a primary diagnosis code for cardiac arrest ( ICD-10 code I46.x). The positive predictive value of this definition was 92.1%. 19 The exclusion criteria were as follows: (1) age younger than 18 years, (2) survival for less than 1 year, or (3) cardiac arrest due to traumatic or nonmedical causes ( ICD-10 S, T codes), such as injuries, poisoning, asphyxiation, burns, or anaphylaxis. In addition, we excluded patients who had a code for depression or anxiety within 3 years of cardiac arrest as a washout period to target newly diagnosed patients after OHCA.

Follow-up data were obtained for up to 14 years (until December 31, 2018) and were analyzed, and the primary outcome was long-term cumulative mortality. In addition, the data of patients diagnosed with depressive or anxiety disorder within 1 year were extracted, and the diagnoses of depression and anxiety were confirmed in patients who visited an outpatient clinic or hospital on at least 1 occasion by the presence of ICD-10 diagnostic codes F32.x (depression) and/or F41.x (anxiety). The date on which the diagnostic code was first entered was regarded as the time of diagnosis. Then, we compared the long-term survival rates among the total group diagnosed with depression or anxiety, group diagnosed with depression, group diagnosed with anxiety, and the undiagnosed group.

The independent variables included age category, sex, and the Charlson Comorbidity Index (CCI) score. The CCI score was calculated at the time of diagnosis within 1 year before the index date using the Quan algorithm. 20 , 21

Several variables were included in the analysis. First, in this study, we examined long-term mortality in patients with newly diagnosed depression or anxiety among those who survived after OHCA. However, additional analysis was conducted on whether a diagnosis of depression or anxiety before OHCA was associated with long-term mortality. Second, there may be many factors associated with long-term mortality in patients who survived after OHCA. Among them, we additionally classified the diagnosis codes of myocardial infarction, and the prescription codes of antipsychotics, antidepressants, and sedatives and analyzed the long-term mortality of patients including these variables. Third, we analyzed the causes of mortality of patients who survived after OHCA. Accordingly, we further classified them into cardiovascular mortality, noncardiovascular mortality, and injury.

The data were analyzed using R, version 4.0.4 (R Foundation for Statistical Computing) and SAS, version 9.4 (SAS Institute Inc). Analysis was conducted on April 7, 2022, and again January 19-20, 2023. Anderson-Darling tests were performed for variables with normal distributions in all data sets. Descriptive statistics were used to describe the baseline characteristics of the patients. Categorical variables are presented as frequencies and percentages and continuous variables as medians (IQRs) or means (SDs) . Independent t tests or Mann-Whitney tests were used for comparisons of continuous variables; the Fisher exact test was used for categorical variables. The cumulative mortality was estimated by the Kaplan-Meier method.

Multivariable Cox proportional hazards regression analyses were used to identify predictors of long-term mortality. Multivariable regression analysis was performed separately for each group, and the results are presented as adjusted hazard ratios (aHRs) and 95% CIs. With 2-sided, unpaired testing, differences were considered statistically significant at P  < .05.

We enrolled 2373 patients after OHCA who had survived for 1 year or longer ( Figure 1 ); median age was 53.0 (IQR, 44.0-62.0) years, 513 (21.6%) were women, and 1860 (78.4%) were men. The median follow-up was 5.1 years (IQR, 3.6-7.2 years). The baseline characteristics of the groups diagnosed and not diagnosed with depressive or anxiety disorder are summarized in Table 1 . A total of 1976 patients did not receive a diagnosis of depression or anxiety, 397 (16.7%) patients were diagnosed with depression or anxiety, 251 (10.6%) were diagnosed with depression, and 227 (9.6%) were diagnosed with anxiety. The baseline characteristics of the groups diagnosed and not diagnosed with depressive disorder and diagnosed and not diagnosed with anxiety disorder are summarized in eTable 1 and eTable 2 in Supplement 1 . There were no significant differences in age category, sex, or CCI score between the groups. The incidence of long-term mortality was higher in the group diagnosed with depression or anxiety than in the group not diagnosed with depression or anxiety (141 of 397 [35.5%] vs 534 of 1976 [27.0%]; P  = .001).

The cumulative mortality rate of patients diagnosed and not diagnosed with depressive or anxiety disorder is presented in Figure 2 ; the cumulative mortality was significantly higher in the individuals diagnosed with depressive or anxiety disorder (long term death, 141 of 397 [35.5%] vs. 534 of 1976 [27.0%]; P  = .002). The cumulative mortality rates among patients diagnosed and not diagnosed with depression and among patients diagnosed and not diagnosed with anxiety are presented in the eFigure in Supplement 1 . The cumulative mortality rate was significantly higher in the group diagnosed with depression (long term death, 94 of 251 [37.5%] vs. 581 of 2122 [27.4%]; P  = .008) than in the group without a diagnosis of depression, but there was no significant difference between the group diagnosed with anxiety and the group without a diagnosis of anxiety (long term death, 72 of 227 [31.7%] vs. 603 of 2146 [28.1%]; P  = .18).

We constructed a multivariate Cox proportional hazards regression model to assess the long-term mortality among patients with OHCA ( Table 2 ). When other known associations were adjusted for age, sex, and CCI score, the aHR of long-term mortality among the total number of patients with depression or anxiety was 1.41 (95% CI, 1.17-1.70); patients with depression, 1.44 (95% CI, 1.16-1.79); and patients with anxiety, 1.20 (95% CI, 0.94-1.53).

In addition, we analyzed the outcomes of the excluded patients who had an ICD-10 code for depression or anxiety within 3 years before OHCA. We performed a multivariable analysis that included this group. As a result, there was no significant difference in the long-term mortality rate of patients who had already been diagnosed with depression or anxiety within 3 years before OHCA compared with those without depression or anxiety (aHR, 1.06; 95% CI, 0.91-1.23). However, the long-term mortality rate among patients diagnosed with depression or anxiety after OHCA was significantly higher (aHR 1.41; 95% CI, 1.17-1.70). Patients with only depression and those with only anxiety disorder within 3 years before OHCA were analyzed separately. The results also showed no significant difference in long-term mortality compared with patients without psychiatric disorders (depression: aHR, 1.09; 95% CI, 0.92-1.29 vs anxiety: aHR, 0.97; 95% CI, 0.83-1.13).

We also classified the causes of death for individuals who survived OHCA as cardiovascular mortality, noncardiovascular mortality, and injury. A total of 272 patients (14.4%) died of cardiovascular-associated causes after OHCA. Fifty-seven of 397 patients (14.2%) with depression or anxiety and 215 of 1976 individuals (10.9%) without depression or anxiety died. In a multivariable analysis including the group of patients with cardiovascular mortality, the aHR of patients with depression or anxiety was 1.41 (95% CI, 1.05-1.89). Noncardiovascular mortality accounted for the deaths of 84 of 397 (21.2%) patients with and 319 of 1976 (16.1%) patients without depression or anxiety. In multivariable analysis, the aHR of patients with depression or anxiety was 1.41 (95% CI, 1.11-1.80). A total of 24 patients died due to injury, 7 of 397 (1.8%) with and 17 of 1976 (0.9%) without depression or anxiety. In multivariable analysis, the aHR of patients with depression or anxiety was 2.34 (95% CI, 0.97-5.68).

Because new problems, such as myocardial infarction, or new medications, such as antidepressants, may have contributed to a late onset of mortality, we additionally classified the diagnosis codes of myocardial infarction and the prescription codes of antipsychotics, antidepressants, and sedatives. We performed a multivariable analysis including the groups of patients with those diagnosis codes or prescription codes. The aHR of patients with depression or anxiety was 1.63 (95% CI, 1.35-1.97), the aHR of patients with depression was 1.57 (95% CI, 1.26-1.95), and the aHR of those with anxiety disorder was 1.47 (95% CI, 1.14-1.88).

To our knowledge, this was the first population-based study to investigate the association between long-term mortality and psychiatric disorders among patients after OHCA. The patients diagnosed with depression or anxiety had a 1.41 times higher long-term mortality rate than those without such psychiatric disorders. The patients diagnosed with depression had a significantly higher long-term mortality rate than those without the diagnosis (aHR, 1.44), whereas there was no significant difference in the long-term mortality rate between patients diagnosed with anxiety and those without this diagnosis.

Of the 2373 patients enrolled in this study, 397 (16.7%) were diagnosed with anxiety or depressive disorder within 1 year after OHCA. Previous studies have reported that the prevalence of psychiatric disorders, such as depression and anxiety, is high among patients surviving cardiac arrest, and Yaow et al 16 performed a systematic review and meta-analysis of such studies. In the general population, the prevalence rates were 12.9% for depressive disorder, 7.3% for anxiety disorder, and 3.9% for posttraumatic stress disorder; among patients who survived cardiac arrest, the prevalence rates were 19.0% for depressive disorder, 26.0% for anxiety disorder, and 20% for posttraumatic stress disorder. In addition, they found that the prevalence of depression and anxiety in patients who survived OHCA increased over time. Specifically, the prevalence of depression increased from 17.0% at 6 months to 30.0% at 12 months and the prevalence of anxiety increased from 34.0% at 6 months to 38.0% at 12 months. The difference in prevalence between this study and previous studies might be explained by the fact that the present study included only patients diagnosed in hospitals. Postcardiac arrest syndrome is estimated to affect both the physiologic and psychological aspects of long-term prognosis in survivors. The unpredictability and severity of OHCA can cause severe life disruptions for patients. 22 , 23 The neurologic deficit caused by ischemia-reperfusion injury following OHCA can create challenges in accomplishing previously simple daily tasks without assistance. 23 , 24 These realities and arduous transformations can cause extreme limitations and despondency. Such life changes can result in a decrease in health-related quality of life, which affects psychological distress. 11 Most patients with OHCA receive immediate therapy in the intensive care unit after the return of spontaneous circulation. After receiving intensive care unit treatment, new or worsening physical and cognitive or mental disorders are referred to as postintensive care syndrome, which is estimated to affect up to one-third of survivors after intensive care unit stays. 25 Hatch et al 26 reported that, among patients who received intensive care unit treatment following critical illness, those with depression had an approximately 50% higher 2-year mortality rate than those without depression.

The increase in the prevalence of depression and anxiety in patients surviving OHCA is important because the increase may be a factor in a higher prevalence of psychiatric disorders and is associated with outcomes such as mortality. Cuijpers and Smit 27 reported that the overall relative risk of mortality in patients with depression was 1.81 (95% CI, 1.58-2.07) compared with those without depression, and depression should be considered a life-threatening disorder. In addition, Zivin et al 28 reported that the HR of patients with depression for 3-year mortality was 1.17 (95% CI, 1.15-1.18), and depression was associated with an increased risk of death due to nearly all major medical causes, regardless of the presence or absence of multiple primary risk factors. Cardiac disease is one of the factors contributing to the high mortality rate among patients with depression. It was reported that patients experiencing psychological distress had a higher incidence of myocardial infarction and worse survival and prognosis outcomes following myocardial infarction than their counterparts. 29 , 30

Previous studies have reported an increase in the incidence of psychological disorders in individuals following OHCA 11 , 15 , 31 but have not noted an association between psychological disorders and mortality in this population. To analyze this association, we obtained long-term follow-up data from a large sample of patients with OHCA; these data were of great value in evaluating the association between psychiatric disorders and long-term mortality.

In the past, there were no specific guidelines for the prevention and treatment of psychological disorders in patients with critical illness or following OHCA. However, the Society of Critical Care Medicine’s International Consensus Conference recently recommended that serial assessments for postintensive care syndrome–related problems continue for 2 to 4 weeks after hospital discharge and should be prioritized among high-risk patients using identified screening tools to prompt referrals for services or more detailed assessments. 32 Recent studies on the rehabilitation requirement for patients who survive cardiac arrest have been performed, and guidelines for the rehabilitation of patients with critical illness have been published. 14 , 16 , 31 Peskine et al 31 advised that a specific rehabilitation program for patients following OHCA or patients at risk of impaired functioning is warranted. Based on data from these studies, the recent International Liaison Committee on Resuscitation guidelines emphasize the importance of psychological as well as physical rehabilitation in individuals who survive cardiac arrest. 10 The ERC and European Society of Intensive Care Medicine guidelines recommends examinations to detect physical and nonphysical impairment in patients after cardiac arrest and, if necessary, prompt rehabilitation. 10 In addition, a recent American Heart Association guideline introduced a new link in the chain of survival: recovery from cardiac arrhythmias, highlighting for the first time the importance of rehabilitation. 5 Because the present study identified an association between psychological dysfunction and an increase in long-term mortality, we believe it provides evidence that psychological rehabilitation of patients with OHCA is crucial. In addition, we noted that providing adequate rehabilitation benefited not only the patient's health-related quality of life but also long-term survival.

This study has several limitations. First, the clinical information on patients with OHCA could not be evaluated because this study used claims data from the NHIS. Variables that could affect the outcomes in patients with OHCA, such as shockable rhythm, bystander cardiopulmonary resuscitation, and the duration of cardiac arrest, could not be identified in our study. Second, the results of this study might be biased by potential confounders, such as treatment initiation after depression or anxiety and a lifestyle pattern with low levels of physical activity and appetite and the presence of sleep disturbances. Third, new medical problems and new medications may contribute to the causes of long-term mortality, but we were unable to adjust for all variables. Fourth, because this study was performed using diagnostic codes, it was impossible to include those who did not receive a diagnosis of depression and anxiety disorders because they did not visit the hospital. Fifth, the diagnosis of OHCA and cause of death were defined using ICD-10 codes, and we cannot rule out diagnostic inaccuracies. In particular, the identification of patients with OHCA and in-hospital cardiac arrest can be inaccurate. We confirmed the definition of OHCA, but the small sample size is a limitation.

Among patients who survived OHCA, those diagnosed with a psychiatric disorder had a higher long-term mortality rate. The findings of this study suggest that it may be important to provide psychological as well as neurologic rehabilitation to individuals after OHCA to help improve long-term survival.

Accepted for Publication: February 22, 2023.

Published: April 12, 2023. doi:10.1001/jamanetworkopen.2023.7809

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Lee J et al. JAMA Network Open .

Corresponding Author: Jaehoon Oh, MD, PhD, Department of Emergency Medicine, College of Medicine, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea ( [email protected] ).

Author Contributions: Dr Oh had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs J. Lee and Cho contributed to this study equally as first authors.

Concept and design: J. Lee, Cho, Oh, Kang, Lim, S.H. Lee.

Acquisition, analysis, or interpretation of data: Cho, Ko, Yoo, S.H. Lee.

Drafting of the manuscript: J. Lee, Kang, S.H. Lee.

Critical revision of the manuscript for important intellectual content: Cho, Oh, Lim, Ko, Yoo, S.H. Lee.

Statistical analysis: J. Lee, S.H. Lee.

Administrative, technical, or material support: Kang.

Supervision: Cho, Oh, Kang, Lim, Ko, Yoo.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by National Research Foundation of Korea grant NRF-2022R1A2C1012627.

Role of the Funder/Sponsor: The National Research Foundation of Korea 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 decision to submit the manuscript for publication.

Disclaimer: This study used the National Health Insurance Service database (NHIS-2022-1-580). The interpretations and conclusions reported herein do not represent those of the National Health Insurance Service.

Data Sharing Statement: See Supplement 2 .

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83% of Adults With Generalized Anxiety Disorder Symptoms Are Undiagnosed

N EW YORK CITY -- Almost a quarter of surveyed U.S. adults met criteria for generalized anxiety disorder (GAD), though the vast majority of them were undiagnosed, a retrospective cross-sectional study suggested here.

Out of 75,261 respondents to the online 2022 National Health and Wellness Survey, 23.3% screened positive for anxiety using the 7-Item GAD Questionnaire , Daniel Karlin, MD, chief medical officer of MindMed in New York City, reported here at the American Psychiatric Association annual meeting.

Of those who screened positive, 83.1% had never received a GAD diagnosis. Most (55.1%) of the individuals screening positive had moderate symptoms while 44.9% had severe symptoms.

Last year, the U.S. Preventive Services Task Force recommended that all adults up to age 64 be screened for anxiety in the primary care setting, including for GAD, in order to avoid delays in diagnosis and treatment. But Karlin explained that estimates of undiagnosed GAD had been outdated or based on small samples.

If the proportions identified by Karlin and his team were broadened to the entire U.S. population, it would represent around 59 million adults with GAD, 49 million of whom are undiagnosed.

"There are a lot of people walking around with symptoms that are severe enough for them to have moderate to severe GAD who've never been diagnosed," he told MedPage Today . "The burden of illness of undiagnosed GAD is remarkably high."

"These findings reflect something that we're missing as a healthcare system, that there are people who have this severe anxiety, they aren't sure what to do [or] what there is to be done about it," he said. "We need to be doing a better job of screening for anxiety disorders, and then intervening when we detect them."

Karlin said that for a long time there has been a greater focus placed on diagnosing and treating major depressive disorder (MDD), but GAD and MDD are "overlapping diseases," he noted.

"We need to continue to recognize that distress comes in different flavors, and that no single flavor is more important than any other," Karlin added. "Let's make sure we're paying attention to anxiety as well as depression."

A few characteristics stood out among adults with GAD who were undiagnosed. They were more likely to be younger, male, smokers, alcohol drinkers, employed, and have a higher income when compared with controls without GAD symptoms or those already diagnosed with GAD:

• Age: 37.5 vs 51.8 vs 42.1 years, respectively
• Male: 54% vs 49% vs 26%
• Current smoker: 36% vs 15% vs 23%
• Alcohol drinker: 72% vs 64% vs 65%
• Employed: 75% vs 55% vs 50%
• Income of $75,000 or higher: 59% vs 46% vs 26%

The group with undiagnosed GAD were also less likely to be white (51% vs 65% vs 69%, respectively) and less likely to have overweight or obesity (45% vs 62% vs 68%).

Karinn Glover, MD, MPH, a psychiatrist at Albert Einstein College of Medicine in New York City, wasn't surprised to see people with GAD report higher rates of alcohol use, pointing out how untreated anxiety is linked with substance use.

"I certainly wonder how many of those who screened positive for anxiety also have relied heavily on alcohol or cannabis to manage anxiety and to what extent that use might meet criteria for misuse or a disorder," Glover, who wasn't involved with the research, told MedPage Today .

In another poster presented here led by Karlin and colleagues, adults with undiagnosed GAD also tended to have a poorer quality of life. Compared with diagnosed adults, undiagnosed adults had significantly fewer healthcare provider visits in the past 6 months (3.0 vs 8.7) but had a significantly higher number of hospitalizations (1.2 vs 0.3) and emergency room (ER) visits (1.3 vs 0.5; P <0.001 for all).

The Work Productivity and Activity Impairment Questionnaire also showed that undiagnosed adults had scores for absenteeism, presenteeism, overall work productivity impairment, and activity impairment that were 3.1, 1.9, 1.9, and 1.6 times higher, respectively, than diagnosed adults ( P <0.001 for all).

As for RAND-36 Physical, Mental, and Global Health Composite scores, undiagnosed adults trended toward lower but not significantly different physical (36.1 vs 39.6) and global health composite scores (32.3 vs 33.5), but higher mental health composite scores (32.8 vs 32.1).

Interestingly, adults with undiagnosed GAD were less likely to report certain comorbidities like depression (15% vs 79%) and pain (10% vs 44%) than diagnosed adults.

In order to catch more cases of undiagnosed anxiety, Karlin recommended healthcare providers screen patients using the 7-Item GAD Questionnaire. Agreeing, Glover said these findings support the use of the collaborative care model -- a brief anxiety screening at every primary care visit followed by a warm handoff to a clinician providing evidence-based treatment in the primary care setting for each patient who screens positive and is interested.

"Collaborative care decreases barriers like waitlists and avoids some of the stigma often associated with obtaining care in more specialized psychiatric settings," Glover said. "Additionally, screening in primary care has been shown to decrease healthcare costs like ER visits in the long run."

Both studies were funded by MindMed.

Karlin and several co-investigators reported employment with MindMed. No other disclosures were reported.

Glover had no disclosures.