National Institute on Aging’s 50th Anniversary: Advancing Cognitive Aging Research and the Cognitive Health of Older Adults

Abstract

In celebration of the National Institute on Aging’s (NIA) 50th anniversary, this paper highlights the significant advances in cognitive aging research and the promotion of cognitive health among older adults. Since its inception in 1974, the NIA has played a pivotal role in understanding cognitive aging, including cognitive epidemiology, interventions, and methods, for measuring cognitive change. Key milestones include the shift toward understanding cognitive impairment and Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRD), the development of large-scale longitudinal studies, and the incorporation of AD/ADRD-related biomarkers in cognitive aging cohorts. Additionally, NIA has championed diversifying the scientific workforce through initiatives, such as the Resource Centers for Minority Aging Research and the Butler-Williams Scholars Program. The next 50 years will continue to emphasize the importance of inclusion, innovation, and impactful research to enhance the cognitive health and well-being of older adults.

On May 31, 1974, Congress passed Public Law (PL) 93-296 authorizing the establishment of a National Institute on Aging (NIA) leading to the official establishment of the institute on October 7, 1974. Since its inception, NIA has been dedicated to supporting groundbreaking research to help improve the health and well-being of older adults. In doing so, NIA’s work has led to important scientific discoveries about the aging process, age-related diseases and conditions, and the needs of the growing older adult population. In addition, NIA’s commitment to fostering a diverse and inclusive aging-focused workforce has helped to develop and train scientists across the translational research spectrum and to establish centers programs and research networks throughout the world. One example of the former is the Resource Centers for Minority Aging Research, a program designed to increase diversity among scientists who conduct social, behavioral, psychological, and economic research on aging. Another program dedicated to enhance the diversity of the workforce is the Butler-Williams Scholars Program, through which NIA provides unique opportunities to junior faculty and new researchers in the field to expand their networks, improve grant-writing skills, and gain a broader understanding of aging research. NIA also offers multiple individual fellowships and career development programs, and institutional training and research education that strongly encourage the participation of individuals from diverse backgrounds.

Cognitive Aging

Cognitive health—the ability to clearly think (i.e., process information), learn, remember, organize, plan, solve problems, and make decisions—is important to maintaining the ability to perform everyday tasks and engage in meaningful activities. Cognitive health is just one aspect of overall brain health, with the latter concept also including an emphasis on reducing the formation of potentially harmful neuropathology. Cognitive aging is a process of gradual, evolving, yet highly variable changes in cognitive functions that occur as people age. Cognitive aging is a lifelong process, not a disease (Institute of Medicine, 2015). Many of our thinking abilities appear to peak around age 30 and, on average, show subtle decline with age (Harada et al., 2013; Hartshorne & Germine, 2015; Salthouse, 2019; Schaie et al., 2005). These age-related declines most commonly include decreases in the speed of cognitive processes that affect thinking, difficulties sustaining attention, multitasking, holding information in mind, as well as word-finding. However, not all thinking abilities decline with age. In fact, vocabulary, reading, and some forms of verbal reasoning remain unchanged or even improve during the aging process (Healthy Aging, n.d.). NIA’s Division of Behavioral and Social Research (BSR) in collaboration with the NIA Division of Neuroscience currently supports research in five broad areas of research, specifically cognitive epidemiology, cognitive interventions, methods for measuring cognitive change, experimental cognitive aging research, and applied cognitive research. Collaboration between these two NIA divisions has increased over the years, including joint initiatives such as the Cognitive Aging Summits (https://www.nia.nih.gov/research/dn/cognitive-aging-summit-iv; in collaboration with the McKnight Brain Research Foundation and the Foundation for the NIH) and Notices of Funding Opportunities and Requests for Applications on neural and behavioral profiles of cognitive aging.

Due to the enhancement of larger scale, often nationally representative longitudinal studies to include more careful measurement of cognitive status and, increasingly, in the collection of biospecimens that can support the measurement of AD-related biomarkers, the cognitive epidemiology portfolio has shifted notably away from focusing only on normal cognition to allowing these significant data infrastructure investments to inform our understanding of age-related cognitive impairment and dementia. Thus, the portfolio has come to focus on finding behavioral and social risk factors that could signal future cognitive impairment even in early adulthood and/or behavioral and social outcomes related to declines in cognition. More recently, NIA has invested heavily to increase the cognitive and dementia relevance of a series of longitudinal educational cohorts studies, including the long-running Wisconsin Longitudinal Study, a revival of the Sputnik era Project TALENT, The National Longitudinal Study of 1972 (NLS72), The High School and Beyond Study (1980), and, most recently, the Add Health study initially supported by the National Institute of Child Health and Human Development. This collection of studies allows interested researchers to pursue true Age-Period-Cohort analyses of the risk and protective factors influencing cognitive health. NIA has invested in the Health and Retirement Study (HRS) International Family of Studies and the Harmonized Cognitive Assessment Protocol (https://www.nia.nih.gov/research/dbsr/global-aging/hrs-international-family-studies-and-harmonized-cognitive-assessment-protocol) to facilitate cross-national comparisons that will help us understand how economic, institutional, policy, social, and cultural factors influence aging and AD/ADRD-related outcomes. The U.S. Health and Retirement Study (HRS) International Family of Studies includes the HRS, which longitudinally follows a population representative sample of U.S. adults over the age of 50 and their partners, as well as a growing number of HRS partner studies in over 40 countries around the world including Mexico, England, Northern Ireland, India, the European Union (EU), China, South Africa, and Brazil. Although the HRS studies include cognitive data, given the increasing interest in AD/ADRD the Healthy Cognitive Aging Project (HCAP; King, 2019) was developed to provide data that would allow comparable diagnostic classifications of mild cognitive impairment (MCI) and dementia across countries. While in most HRS countries, the HCAP is administered to a subsample of the HRS sample, the subsample is nationally representative and diagnostic classification can be projected to the entire sample. HCAP studies have been completed in the United States, Mexico, England, India, China, Chile, and South Africa and are underway in the Dominican Republic, EU (Denmark, Czech Republic, Germany, France, Italy), Ireland, Lebanon, Nepal, and Northern Ireland. Pilot HCAP studies are underway in Ghana, Kenya, and Egypt. NIA also supports educational cohort studies seeking to understand education and other social factors as risk and protective factors for dementia across the life course. NIA has also launched a new funding initiative to enhance measures of educational exposures and cognitive assessments in existing studies to support this work. A new coordinating center to foster collaboration and accelerate life-course research on the social, behavioral, economic, and environmental exposures that shape AD and ADRD outcomes and inequities, will be established in 2024 (RFA-AG-24-011; https://grants.nih.gov/grants/guide/rfa-files/RFA-AG-24-011.html). Finally, NIA has historically supported cognitive training intervention research, most notably the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial. The ACTIVE trial was the first large-scale, multisite randomized trial to look at the efficacy of different types of cognitive training (memory, reasoning, speed of processing) on cognitive performance and everyday functioning among relatively healthy older adults, with follow-ups extending 5- and 10-year post-intervention. The ACTIVE trial showed cognitive training can delay or slow age-related cognitive decline on reasoning, speed of processing, and maintenance of independence in instrumental activities of daily living (IADLs) in older adults (Rebok et al., 2014). The trial strongly supports the potential for cognitive training interventions, but further research is needed as meta-analyses show inconsistent, small-to-moderate effects for tasks similar to those used during training and sparse evidence for substantially different tasks or IADLs (Basak et al., 2020; Livingston et al., 2020; Rebok et al., 2014; Sala & Gobet, 2019). Further, Preventing Cognitive Decline and Dementia: A Way Forward, the report by the National Academies of Sciences, Engineering, and Medicine (2017) concluded the evidence for cognitive training on maintenance of cognitive function is encouraging but inconclusive, requires further study, and there is no RCT evidence that cognitive training will prevent, delay, or slow MCI or AD/ADRD.

Alzheimer’s Disease and Alzheimer’s Disease-Related Dementias

The first Alzheimer’s Disease Research Centers were introduced in 1984. Now, NIA is the lead federal agency for AD/ADRD research to prevent these diseases, improve cognitive and brain health outcomes in those with AD/ADRD, decrease the emotional/health burdens on those serving as caregivers, and address the economic burdens associated with AD/ADRD, especially those experiencing health disparities and inequities in care.

It is estimated that over 6 million Americans have AD, and the prevalence of AD is expected to more than double to 13.85 million by 2060 in the absence of successful prevention and treatment efforts (2022 Alzheimer’s disease facts and figures, 2022). Cognitive and dementia epidemiology studies focus on the social, economic, environmental, and regional factors that drive national prevalence and incidence of AD/ADRD, as well as national estimates of costs associated with dementia care. This includes international population-based studies that permit cross-national comparisons of cognitive decline, dementia prevalence, incidence, and risk/protective factors where the interrelationships between environmental exposures, behavioral and social processes, biological (including genetic) risk, and later-life cognitive impairment are investigated.

Prior to the clinical diagnosis of AD/ADRD, individuals may experience subtle changes in cognition, emotion, social behavior, or changes in everyday functions, like financial decision making, driving, or medication management. NIA has invested in developing sensitive tools for early detection of these psychological and functional changes. Such tools could inform the development of new diagnostic procedures, identify individuals who might benefit from treatments or preventive interventions, and allow people to take steps to manage important decisions about healthcare, finances, driving, and living arrangements (Behavioral and Social Research on Alzheimer’s Disease & Alzheimer’s Disease Related Dementias, 2024). Critically, it will help identify what matters most to participants in our studies and trials (Clinically Meaningful Outcomes in AD/ADRD Trials, 2024). This includes preserving cognitive health, stopping or delaying disease, improving function, remembering family, remaining independent, removing disease pathology, and prioritizing return of research results (DiBenedetti et al., 2020; Walter et al., 2022).

Detection of Early Cognitive Change

Earlier diagnosis of cognitive impairment, including accurate and accessible measurement of cognitive change, will allow for greater opportunity for intervention, including testing the efficacy of our therapies and delivering information about cognitive function and change to research participants in our studies. To precisely characterize intraindividual change, assessments need to capture the time and context-dependent nature of human behavior and performance, which exhibit meaningful variations across various timescales and in response to changes in human function and the contexts of function. Advances in digital and mobile technologies create opportunities for enhancing measurement of intraindividual change by enabling high-frequency assessment in an individual’s daily environment.

Because most existing research has focused on group-level data, we are still missing answers to fundamental questions about cognitive change across the lifespan: What are individual-level change trajectories? Is normal cognitive aging on the individual level a continuous process, or does it involve discreet change points? What is the dimensionality of individual-specific cognitive change? Without clear answers to these questions, it remains very difficult to address problems of great practical and clinical importance, such as: How can we detect pathological deviations from typical aging? How frequently do we need to test an individual? How many different cognitive functions and which noncognitive factors need to be measured to robustly assess cognitive change? How do we best assess whether cognitive change has affected meaningful, real-world function? How should we leverage advances in measures and measurement methods to optimize assessment of cognitive change, especially changes due to aging, disease (e.g., AD/ADRD), and response to intervention over time?

For example, how do we detect and track subjective cognitive decline and mild cognitive decline (e.g., MCI) that may occur in advance of a clinical dementia diagnosis and how do we differentiate this from age-related or developmentally normative change at the individual level? What are the contexts of use for cognitive change measures and how do we validate for individual-level inference in a context-dependent manner? We don't have a gold standard for detecting cognitive change. What are the minimum viable performance criteria for use if there is no reasonable and appropriate gold standard, especially in light of our modern diagnostic ecosystem that will increasingly rely on digital, mobile, and artificial intelligence and machine-learning-enabled measurement tools and methods?

Recent Advancements (2019–2024)

The past 5 years have been marked by remarkable progress in cognitive aging research. NIA’s commitment to understanding and mitigating cognitive decline has led to several notable achievements:

Cognitive Testing Infrastructure

Mobile Toolbox (MTB; https://mobiletoolbox.org) is a new tool that researchers can use to conduct digital tests of cognition through a smartphone app. It is designed to be easy to use, and it can be self-administered remotely in participants’ homes and other nonclinical settings. The MTB provides reliable, consistent, performance-based measures of cognition across the lifespan. Moreover, it’s a research platform that scientists can use to develop apps that include additional measures beyond those in MTB, manage studies, and collect and organize data using the REDCap system (https://www.project-redcap.org) already in wide use.

The Advancing Reliable Measurement in Cognitive Aging and Decision-Making Ability (ARMCADA; https://sites.northwestern.edu/armcada) network aims to develop a taxonomy of decision-making skills for successful aging, establish new measures of decision making, and facilitate scalable nationwide public dissemination of these measures to benefit the early identification of older adults with cognitive impairment and evaluate the efficacy of potential interventions aimed to mitigate cognitive decline commonly associated with AD/ADRD.

The Open Measurement Coordinating Network for Non-Pharmacological AD/ADRD Primary Prevention Trials (https://grants.nih.gov/grants/guide/rfa-files/RFA-AG-25-005.html) will serve as a centralized hub for developing, validating, standardizing, and disseminating measures and measurement methods for AD/ADRD primary prevention trials. It will incorporate measures and measurement methods across neuropsychological, biomarker, and functional domains to meet the goal of primary prevention of AD/ADRD centered around brain health equity. Measures and measurement methods of interest will test outcomes and mechanisms of action (e.g., cognitive, behavioral, structural/social, computational, biological) that are customized for individuals with different needs and that are linked to real-world function. Resources developed through this initiative, including measurement instruments, methods, algorithms, code, documentation, and normative data, are intended to enable future measures and measurement methods development projects that support AD/ADRD primary prevention research needs.

Cognitive Interventions

NIA is committed to further support efforts in cognitive training research, with targeted investments such as the Preventing Alzheimer’s Disease with Cognitive Training (PACT) trial (https://pactstudy.org) and the Adaptive Clinical Trial of Cognitive Training to improve Function and Delay Dementia (ACTIVE Mind) trial (https://clinicaltrials.gov/study/NCT04171323). The PACT trial will test the effectiveness of speed of processing training to reduce incidence of MCI or dementia in cognitively normal older adults and the Active Mind trial will compare combinations of cognitive training to determine which combination will improve everyday function among persons with MCI and determine if cognitive training lowers ADRD risk among those with MCI. Additionally, in Summer and Fall 2024, NIA will lead a Cognitive Training Webinar Series (https://www.nia.nih.gov/research/dbsr/workshops/cognitive-training-webinar-series) that will explore key issues in cognitive training and address high-priority research questions with the goal of identifying research gaps and opportunities to advance the field.

Integration of Technology

The use of technology in cognitive aging research has expanded, with initiatives like Mobile Monitoring of Cognitive Change (U2C; https://grants.nih.gov/grants/guide/rfa-files/RFA-AG-18-012.html) leveraging digital tools to enhance the measurement of cognitive changes.

Technology-based multimodal sensing (e.g., smart phone, wearables, in-home, other pervasive sensing), which allows continuous and concurrent capture of free-living behavior and context, when combined with AI/ML approaches, provides a powerful way to advance dynamic behavior measurement, including prediction of change. An NIA-led webinar (Landscape of Early Neuropsychological Changes in AD/ADRD Webinar Series; https://www.nia.nih.gov/research/dbsr/workshops/landscape-early-neuropsychological-changes-ad-adrd-webinar-series) and working group is developing next steps to leverage DHTs for comprehensive free-living behavior research, which will generate new insights necessary to improve the detection of AD/ADRD, better characterize disease progression, and aid the development of interventions to improve the quality of life of the individuals affected by AD/ADRD.

Just-In-Time Adaptive Interventions (JITAIs) use mobile and sensor-based technologies to monitor individuals and provide timely support when a person is most in need and receptive to it. These interventions require monitoring the individual to decide whether the individual is in a state that requires support, what type (or amount) of support is needed given the individual’s state, and whether the person is receptive (i.e., likely to engage effectively with) this type of support (Nahum-Shani et al., 2018). Immersive VR, smart devices, and web applications, and AI-assisted digital interventions like cognitive training offer potential companion tools that could be used with traditional intervention and care support. However, there are no robust studies demonstrating the efficacy of such systems in older adults, especially when considering long-term health outcomes (Workshop on Applying Digital Technology, 2019).

Gaps and Opportunities

Despite these advancements, several challenges remain:

Health Disparities and Cognitive Health Equity

The 2019 National Advisory Council Review of BSR (National Advisory Council on Aging, 2019) recommended that future research go beyond documenting health disparities and seek to identify the causal drivers of those disparities and develop approaches to ameliorate them. This includes a specific focus on AD/ADRD health disparities (AD/ADRD Health Disparities, 2024) in cognitive health. Cognitive health equity is the fair distribution of cognitive health determinants, outcomes, and resources within and between segments of the population, regardless of social standing. Addressing equity concerns, includes a focus on inclusion of diverse communities in: the design, development, validation, and dissemination of all cognitive assessment methods and tools; the research team; research participants; community advisors; and community partners. There is an imperative to maximize accessibility of methods and tools (across devices, age, race/ethnicity, languages, education levels, ability levels, and resource levels) and identify bias and barriers to generalizability of methods and tools, including comprehensive documentation of both steps taken to mitigate bias and broaden generalizability, as well as careful documentation of any potential biases or limits to generalizability (e.g., populations where full validation has not yet been conducted) that can be disseminated to users and updated as appropriate as new issues are identified, and existing issues are addressed. Finally, it is important to acknowledge, identify, and address gaps in understanding the impact of structural racism on cognitive function across the lifespan.

Complexity of Dementia

AD/ADRDs are heterogeneous diseases with diverse underlying pathologies. Understanding the cognitive phenotypes for the AD/ADRDs, relationship to these different underlying pathologies, and how this impacts the trajectory and course of cognitive change remains a priority.

Training and Workforce Development

As we look ahead to the future, training will continue to remain a priority for NIA. NIA offers multiple individual fellowships and career development programs, and institutional training and research education that strongly encourage the participation of individuals from diverse backgrounds. However, in an effort to increase our outreach efforts to recruit the next generation of scientists we need to continue to foster engagement with students when they are in middle and high school. We also need to continue to improve relationships with groups that have traditionally been under-represented in research, including those who continue to have mistrust in science. This includes African Americans (Blacks), American Indians and Alaska Natives, Hispanics (Latinos), Native Hawaiians and other Pacific Islanders (Women, Minorities, and Persons with Disabilities in Science and Engineering, 2019).

Future Directions

As NIA looks forward to the next fifty years, it is exciting to see the following areas of focus emerging in the field:

Open Science to Advance Access and Use of Real-World Data

Open science is, in part, an emergent property that grew out of the need for data, infrastructure, and tool sharing (Tim Errington, personal communication). Open, accessible, inclusive, and integrated measurement approaches for mechanisms identification and testing of meaningful outcomes will continue to shape research efforts. Advances in digital health technologies (DHTs) are revolutionizing studies by enabling real-world, high-frequency, longitudinal data collection, which can accelerate the development and testing of new assessment methods and tools and increasing participation of under-represented participants by improving access and engagement. Efforts like the Open Measurement Coordinating Network for Non-Pharmacological AD/ADRD Primary Prevention Trials will be using these principles and practices to advance cognitive assessment and health.

Artificial Intelligence and Machine Learning

Artificial Intelligence (AI)-driven measurements are another promising area, where AI, combined with digital measures and phenotypes, could identify, and predict patterns, improve diagnosis, monitor disease progression, and response to intervention. Digital metrics, including digital biomarkers, are objective, quantifiable physiological, cognitive, psychological, social, and behavioral data collected using digital technology. However, there are challenges to be addressed, including limited interpretability of machine learning (ML)/AI models, integration with traditional research methods, access to diverse and longitudinally collected datasets, clinical validity and utility in real-world settings, and collaborative efforts between researchers, clinicians, policymakers, and industry partners. A special issue in the Psychological Sciences section of The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences (https://academic.oup.com/psychsocgerontology/pages/call-for-papers-ai-driven-measurement) is being developed by the NIA Landscape of Early Neuropsychological Changes in AD/ADRD Working Group to articulate, organize, and prioritize these challenges. In the context of aging, AI has many potential important applications, including early detection of age-related cognitive decline and changes due to AD/ADRD, tailoring lifestyle strategies for prevention of age-related diseases, including AD/ADRD, assisting patients and care partners in managing behavioral and psychological symptoms of dementia. Now with the ever-increasing advancement of technology, more research studies are including ML, large language models, and AI. This is especially the case with NIA Small Business Programs (SBIR/STTR). The NIA Small Business Programs manage the largest source of early-stage funding for aging-related research and development (R&D). Recently, these programs have been expanded to include entrepreneurial education programs that are designed to broaden the skillset of graduate students and postdocs as well as early-career master’s degree, PhD, and DrPH scientists in fields relevant to the NIA mission (NIA Research and Entrepreneurial Development Immersion; https://www.nia.nih.gov/research/training/nia-research-and-entrepreneurial-development-immersion-redi).

Mechanisms-Focused Just-in-Time Adaptive Intervention Development

Building on the multiphase optimization strategy, control engineering is a new approach for optimizing individualized adaptive interventions based on systems science principles (Erik Hekler; https://prevention.nih.gov/education-training/methods-mind-gap/using-control-systems-engineering-optimize-adaptive-mobile-health-interventions). Factorial designs and leveraging frameworks, such as Experiment-in-a-Box, can be used to test cognitive health behavior theory and interactive technology design to develop time-limited interactive cognitive interventions. This fits within the mechanisms-focused approach of the NIH Stage Model for Behavioral Intervention Development (https://www.nia.nih.gov/research/dbsr/nih-stage-model-behavioral-intervention-development) offering a powerful future framework for digital cognitive health intervention development.

Precision Cognitive Health and Precision AD/ADRD Prevention

The complexity of AD/ADRD, including an increasing emphasis on prevention, underscores the importance of personalized cognitive health. Delivering the right treatment at the right time for each individual will be a cornerstone of future research.

Conclusion

The NIA has made tremendous contributions to cognitive aging research over the past 50 years. As we look ahead, NIA’s commitment to inclusive, innovative, and impactful research promises to further enhance the cognitive health and well-being of the aging population. By building on past successes and embracing future opportunities, NIA will continue to lead the way in extending and enhancing the healthspan and quality of life for older adults.

Funding

None.

Conflict of Interest

None.

Data Availability

This article does not report data and therefore preregistration and data availability requirements are not applicable.

Disclaimer

The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health or federal government.