Many mental health conditions develop during youth and adolescence, making it a global public concern [1-3]. The number of young people experiencing mental health issues continues to rise. According to the Centers for Disease Control and Prevention (CDC), the percentage of high school students reporting feelings of sadness and hopelessness increased significantly over the past decade, rising from 28% in 2011 to 40% in 2023 [4]. This marked increase highlights a growing mental health crisis among adolescents, emphasizing the urgent need for prevention and early intervention. Adolescence is a period of significant psychological, emotional, and social development, making it a critical window for addressing mental health concerns [5]. When left unaddressed, these issues can lead to long-term worse consequences, including impaired educational attainment, strained relationships, and adverse health outcomes in adulthood, far beyond adolescence. In 2021, the U.S. Office of the Surgeon General released an advisory titled “Protecting Youth Mental Health,” emphasizing the urgent need to address the mental health challenges faced by young people [6].

Young individuals with substance use disorders are at an elevated risk of developing co-occurring mental health challenges, including suicidal behaviors, which can exacerbate lifelong difficulties, contribute to social issues, and result in poorer treatment outcomes [7,8]. Preventable mental health issues, such as adolescent suicide [9,10] and substance use [11,12], significantly contribute to youth disease, disability, and mortality, highlighting the importance of proactive measures in urgent need to save lives and improve the well-being of young people. Suicide, one of the leading causes of death among young people, is often preventable through the timely identification of warning signs, access to supportive networks, and evidence-based interventions [10]. Similarly, substance use disorders, which frequently emerge during adolescence, can be reduced through early preventive strategies that focus on education, community support, and behavioral health services [12]. Investing in preventive mental health care during adolescence yields far-reaching benefits [13], not only for affected individuals at the time, but also for them later in life, their families, communities, and societies. Effective prevention programs can enhance resilience, reduce stigma, and promote mental well-being, ultimately fostering healthier and more productive generations overall.

A significant gap persists between the mental health needs of children and adolescents in the United States and the availability of services to meet those needs [14]. Most young people with mental health conditions do not seek or receive treatment [15]. Barriers include limited awareness of available services, inaccessibility, insurance coverage issues, insufficient coordinated care, a shortage of specialized providers, unstable living conditions, concerns about confidentiality, and fear of stigmatization [15,16]. Schools have been identified as critical settings for screening, preventing, and treating youth mental health issues, as students spend the majority of their daily time in these environments [5,17]. To address this critical issue, it is essential to strengthen youth-focused mental health services, integrate mental health education into school curricula, and equip educators, parents, and peers with tools to recognize and respond to early signs of distress [5]. By prioritizing prevention and early treatment, we can disrupt the cycle of untreated mental health issues and cultivate supportive environments where young people can thrive.

In alignment with these efforts, evidence-based medicine continues to drive advancements in mental health care [18]. Evidence-based approaches are crucial for addressing youth mental health challenges [19]. To ensure high-quality, impactful research and promote its translation into clinical practice, service delivery, and policy, the National Institute of Mental Health (NIMH) developed its strategic plan for research aiming at achieving these goals [20]. This plan addresses emerging challenges and opportunities by leveraging scientific advances to improve mental health outcomes. Among its 4 goals, Goal 2—“Examine Mental Illness Trajectories Across the Lifespan”—closely aligns with the collection and analysis of mental health data using diverse datasets.

Mental health conditions are multifaceted [21], influenced by a combination of biological factors (eg, brain trauma and genetics), psychological factors (eg, stress and traumatic events), and environmental, social, and economic determinants. Understanding these complexities demands the collection and integration of diverse datasets to capture the full spectrum of influences on mental health, especially for youth. By assembling data that capture biological, psychological, social, and environmental factors, researchers can reveal a more comprehensive picture of mental health conditions, discover patterns, identify at-risk populations, and design targeted interventions that address the unique needs of young people. Notable existing data sources include national surveys such as the Youth Risk Behavior Surveillance System (YRBSS) [22], the National Survey on Drug Use and Health (NSDUH) [23], and the National Survey of Children’s Health (NSCH) [24], large-scale longitudinal studies such as the Adolescent Brain and Cognitive Development (ABCD) study [25], and targeted clinical trials [26] exploring the efficacy of early interventions and prevention strategies.

The growing volume of biomedical data generated by these studies provides a solid foundation for data mining and knowledge discovery to extract meaningful insights across diverse data types [27-30]. The new emerging artificial intelligence (AI) techniques [28], such as machine learning (ML), natural language processing, and especially generative AI [29], are increasingly used to analyze large-scale datasets, identify early indicators of mental health issues, and develop predictive models for conditions such as depression, anxiety, suicide, and substance use disorders. For example, AI is being used to process real-time data from wearable devices [31], social media activities [32], and electronic health records [28] to gain insights into behavioral patterns and risk factors among adolescents. In the mental health domain, AI has been increasingly applied to develop high-quality predictive models and perform advanced data analyses. For example, deep learning techniques have been used with structural magnetic resonance imaging data from large-scale studies such as the ABCD to predict biological sex and identify gender-related variations in brain structure [33]. In addition, AI-driven analyses have been used to assess the effectiveness of telehealth interventions using datasets such as the NSDUH and other Substance Abuse and Mental Health Services Administration (SAMHSA) resources [34].

One significant challenge in data science and AI is the lack of accessible health care data. Electronic health record data are often restricted due to privacy and security regulations, such as Health Insurance Portability and Accountability Act (HIPAA). This limitation highlights the critical role publicly available datasets play in enabling big data analysis and advancing research. These datasets are particularly vital in advancing youth mental health research, where access to comprehensive data is crucial for revealing meaningful insights and discovering new interventions.

With the National Institutes of Health (NIH) data sharing policy, an increasing amount of research data is now available for secondary data reuse, enabling a broader range of studies to build upon existing findings. Datasets such as the YRBSS, NSDUH, NSCH, and ABCD study provide researchers with open access to comprehensive data on behavioral, social, and biological factors that influence mental health. Effectively integrating these datasets will be crucial in deepening our understanding of mental health and developing innovative solutions for prevention and treatment. By leveraging these resources, researchers can collaborate across institutions, validate findings, and accelerate the discovery of new insights. Furthermore, publicly available data facilitate the development of AI-powered tools to identify trends, predict risks, and personalize mental health interventions. This approach can lead to scalable, equitable solutions to address the growing mental health needs of young people worldwide.

This paper aims to review existing publicly available datasets related to youth mental health and provide a detailed directory as a reference tool for researchers interested in integrating diverse datasets for advanced data analysis or AI-assisted discovery across different aspects of youth mental health. By highlighting the scope and potential of these datasets, this paper seeks to guide future research efforts in leveraging diverse data sources to better understand and address the complex challenges facing youth mental health.

In this brief review, we used a multifaceted approach to identify publicly available datasets relevant to youth mental health. As the study does not involve human participants or identifiable personal information, ethics approval was not required, consistent with the guidance from the U.S. Department of Health and Human Services Office for Human Research Protections (45 CFR 46). Figure 1 presents the overall workflow, which includes conducting a structured web search, consulting with librarians, and incorporating knowledge shared by domain experts. The search results were then curated through organizing, formulating, and refining the identified datasets. The resulting directory has the potential to support discovery and evidence-based research in youth mental health.

The structured search included 3 main approaches: (1) targeted search: we conducted focused searches of reputable websites of health organizations, institutions, and government agencies (eg, NIH and CDC). Our search focused primarily on U.S.-based resources; (2) librarian consultation: we collaborated with professional librarians specializing in health and social sciences to identify and verify datasets not readily found in publicly available search engines; and (3) expert knowledge: leveraging our team’s expertise and prior familiarity with youth mental health research, we included datasets we had previously worked with or identified as significant in the field.

For our targeted search, we began with a literature review on PubMed using Medical Subject Headings (MeSH) terms. We conducted 2 separate searches: the first focused on mental health and the second on substance use.

The inclusion criteria were as follows: (1) the article was peer reviewed and written in English; (2) the full text was available; (3) the research was conducted using publicly available datasets, including studies using multiple datasets; and (4) the primary focus was on mental health or substance use. We also included datasets focused on school health policies and systems that, while not containing individual-level mental health data, provide essential contextual information relevant to youth mental health research. These datasets support investigations of structural and environmental influences on mental health outcomes and were included to encourage more integrative and upstream approaches in the field.

The search returned 197 papers for mental health and 294 papers for substance use. All papers were manually reviewed by the first author (HM), who extracted the datasets mentioned in the articles. The results were validated by the second author (XJ). After identifying the datasets, we visited the corresponding websites directly to obtain more detailed information about each dataset. We also consulted our university librarians and one of the authors (CES), an expert in youth mental health, to identify and add additional relevant datasets.

Next, we curated and categorized the identified datasets, providing a detailed and consistent description of each, including the following elements:

A list of publicly available datasets addressing youth mental health and school policies was compiled in Table 1. While this is not a comprehensive list of all available datasets, it includes key resources that are relevant to youth mental health. The CDC initiates, conducts, and supports many national surveys to understand youth mental health, including the YRBSS, School Health Profiles (SHP), School Health Policies and Practices Study (SHPPS), National Health Interview Survey (NHIS), and the National Youth Tobacco Survey (NYTS). Another important agency is the SAMHSA [35] which collects data related to substance use and mental health services, including NSDUH, National Substance Use and Mental Health Services Survey (N-SUMHSS), Mental Health Client-Level Data (MH-CLD), and Treatment Episode Data Set (TEDS). The U.S. Census Bureau also conducts an annual household survey, the NSCH, which provides national- and state-level data on the health and health care needs of children aged 0‐17 years, as well as their families and communities. The NIMH Data Archive is a valuable resource for mental health data, including studies focusing on youth mental health. One such study is the ABCD study, which tracks over 11,000 children starting at ages 9‐10 to examine how factors such as substance use and genetics influence brain development. Another is the Treatment for Adolescents with Depression Study (TADS), along with its follow-up, Substance Use and Other Outcomes Following Treatment for Adolescent Depression (SOFTAD), evaluates treatments for adolescent depression and their long-term effects on substance use and other outcomes. In addition, the Agency for Healthcare Research and Quality (AHRQ) conducts the annual Medical Expenditure Panel Survey (MEPS) to collect data on health care use, costs, insurance coverage, and health status from individuals, families, medical providers, and employers across the United States. The National Data Archive on Child Abuse and Neglect (NDACAN) curates a wide range of datasets related to child maltreatment, including administrative records, survey results, and state- and local-level reports. These datasets provide valuable insights into the prevalence, characteristics, and outcomes of child abuse and neglect, as well as the effectiveness of related systems and services.

Like the ABCD study, there are 2 other local neuroimaging studies: the NKI Rockland Sample (NKI-RS) [54] and the Healthy Brain Network (HBN) [55]. The NKI-RS focuses on understanding brain function and structure across a wide range of conditions, while HBN aims to improve the diagnosis and treatment of mental health and learning disorders by identifying biological markers, such as brainwave signals and imaging data. Both studies provide valuable neuroimaging data to advance research in mental health and cognitive development. Image data from both studies are stored on Amazon Web Services (AWS) S3, providing accessible and scalable storage for large datasets.

The Inter-university Consortium for Political and Social Research (ICPSR) [56], based at the University of Michigan, is one of the world’s largest archives of social science data. It offers extensive datasets for research and education across social, behavioral, and health sciences. These datasets include both publicly available and restricted-access data from single studies, U.S. national surveys, and international studies and surveys. A search for “youth mental health” or “youth substance use” or “adolescent mental health” or “adolescent substance use” on ICPSR returns 362 studies. Table 2 shows 10 randomly selected public-use youth mental health datasets from the ICPSR. For example, Monitoring the Future: A Continuing Study of American Youth, funded by National Institute on Drug Abuse, is a study of the behaviors, attitudes, and values of Americans from adolescence through adulthood. To date, 133 data files are hosted at ICPSR.

Other central repositories for open data from the U.S. government include Data.gov, which are presented in Table 3. The Department of Health and Human Services (HHS) publishes datasets as part of its Open Data program. The primary resource for public access to health-related data is Healthdata.gov, with additional specialized sites available for specific topics, including Data.CDC.gov, OpenFDA, and Data.CMS.gov. Figure 2 summarizes the results.

In addition to the raw data collected, researchers often identify, code, and summarize publicly available research reports and publications within a particular domain (eg, children and adolescent psychotherapy), categorizing them as researcher assertions rather than data assertions [72]. Such literature data, similar to systematic literature reviews, represent another critical form of publicly accessible information. Despite their descriptive nature, they can be used for meta-analyses, understanding the current state of the field, identifying potential research gaps, and conducting other aggregate evidence-based analyses. Common and reliable sources for identifying data or studies include PubMed, Cochrane Library, PsycINFO, Embase, ClinicalTrials.gov, and NIH RePORT for research portfolios.