Skip to main content

Transforming the understanding
and treatment of mental illnesses.

Goal 3: Strive for Prevention and Cures

Man talking with female counselor

We need to develop better ways to prevent and treat mental illnesses. To achieve that goal, we need validated targets for interventions; new methods of intervention; improved methods to match interventions to individuals and populations, including minoritized and marginalized communities; and, strategies for scaling interventions for the greatest public health impact. A target may be a disease mechanism, a factor related to a disease mechanism, or a factor that confers significant risk. Appropriate targets will depend on the intervention modality and the conceptual framework underlying hypotheses about its mechanism of action. Interventions may encompass prevention and treatment, consider all therapeutic modalities (e.g., pharmacologic, psychosocial, behavioral, device-based, biologics), and include structural changes (e.g., policies). Many protective/promotive factors are at intrapersonal and interpersonal levels, such as presence of a trusted adult or cultural connectedness. The socio-ecological levels beyond the individual level are also potent risk factors that underlie mental health disparities. Research should strive to identify strategies for influencing modifiable factors for the development, testing, and implementation of prevention and treatment interventions, including approaches that are relevant and acceptable to communities impacted by health disparities.

Robust clinical studies require testable hypotheses on how an intervention will engage a relevant target. Interventions should aim to modify targets, based on a hypothesis that such modification will result in improved symptoms, behavior, or functional outcomes. Evaluating the relationship between modification of targets and clinical outcomes allows us to fine-tune our understanding of risk for mental illnesses and helps us to prioritize the most promising interventions. This idea underlies NIMH’s experimental therapeutics approach by which interventions serve not only as potential therapies or preventive strategies, but also as probes to generate objective information about mechanisms of illness and/or resilience. Through the experimental therapeutics approach, information from a research study has scientific value relevant to the condition in question, irrespective of the intervention’s success.

Precision in mental health care means that individuals and populations will receive preventive and treatment interventions that are optimally matched to their characteristics and needs, across disease stages, diagnostic categories, cultures, environments, and the lifespan. Optimizing interventions will not only require consideration of symptoms and functioning, but also a broader consideration of etiologies, intervention, preferences of patients and families, and the contexts of intervention delivery.

NIMH supports the development and testing of preventive as well as treatment interventions, recognizing that many mental illnesses begin well before adulthood and often before symptoms appear or daily functioning is impaired. We need preventive interventions for delivery early in the course of illness and early in life for at-risk individuals, plus treatment interventions to mitigate mental illnesses and associated dysfunction at the earliest possible opportunity. NIMH encourages the development and testing of preventive and early interventions that can be delivered in a developmentally appropriate manner (e.g., at known sensitive periods and at key transitions) as early in life as possible and early in the illness course, to prevent or forestall mental illnesses and associated functional impairment.

The following Objectives further define this Goal:

Doctor holding nasal spray bottle

The experimental therapeutics approach focuses not only on testing whether new interventions show clinical benefit, but, more importantly, on a staged approach where researchers initially establish confidence that the intervention is acting on the presumed target in humans, through a dose-dependent relationship, when appropriate. If successful, larger clinical trials would serve to reconfirm target engagement and further assess clinical impact of the potential intervention. If the interventions do not work in the expected manner, negative results are likewise scientifically informative and fundamental. In the case of an intervention engaging the target but failing to demonstrate a clinical effect, the target would be disqualified. If the intervention fails to adequately engage the target, the intervention would be disqualified from further consideration.

The experimental therapeutics framework also recognizes that clinical targets may differ qualitatively and quantitatively throughout the life course. Therefore, there needs to be a strong scientific premise for selecting clinical targets within a particular age range. Additionally, the dose of an intervention that is safe and effective for target engagement may be age- or developmental stage-dependent and should be systematically established in advance of efficacy testing. It is also recognized that multiple targets often need to be engaged to exert beneficial outcomes.

To more effectively develop new preventive and treatment interventions based on novel genomic, engineering, neurobiological, and behavioral advancements, NIMH will support research that employs the following Strategies:

Interest areas include:

  1. Enhancing the predictive value of preclinical assays used to select targets, drug candidates, circuit-based or cognitive/behavioral interventions, devices, and biologics for clinical development.
  2. Developing strategies to identify any missing elements in preclinical data to better inform future clinical trial designs.
  3. Identifying preventive and treatment intervention targets appropriate to age and stage of illness, and testing interventions to modify those targets to prevent or improve symptoms. Putative targets should be based on scientific discoveries that advance our understanding of the mechanisms and trajectories of mental resilience and illnesses.
  4. Developing promising preventive and therapeutic intervention strategies that target specific molecular, cellular, neural circuit, psychological, intrapersonal, interpersonal, social, and other upstream mechanisms driving core domains of cognitive, behavioral, and affective function that are disrupted in mental illnesses, including those that cut across diagnostic categories. Strategies may include pharmacological, psychosocial, device-based, or biologic therapeutic candidates that engage the target of interest. Studies may also evaluate the functional impact of target engagement and off-target effects and determine the optimal parameters (e.g., dose and dosing regimen) needed to achieve functional impact.
  5. Developing novel preventive interventions based on an understanding of risk and protection at the level of the individual and within a developmental and environmental context, and testing whether targeting proximal risk and protective factors, or intervening factors that reduce risk, result in promoting health and preventing illness.

Interest areas include:

  1. Developing and validating quantitative behavioral and neurophysiological measures of target engagement in humans and animals as translational assays linked to functional domains disrupted in and across mental illnesses.
  2. Developing and optimizing reliable and objective measures of target engagement and intervention on brain (molecular, cellular, circuit) function, side effects, clinical symptoms, and functional outcomes that can be implemented in clinical trials.
  3. Testing novel behavioral markers and their associated neural activity patterns as potential stratification measures. Such testing might include computational and bioinformatics approaches and remote sensors.
  4. Optimizing and validating real world outcome measures, including participant-reported outcomes, for use across clinical and non-clinical populations. Such measures may take into account illness phase, age, sex, race, ethnicity, culture, disability, education, socioeconomic background, and other factors.
  5. Developing and assessing novel mobile technology and digital health tools to enable objective measurement of behavior and intervention effects on symptom expression, functional outcomes, and quality of life in naturalistic environments.
  6. Developing valid proxy measures or markers that are relatively brief and cost-effective for use in outcomes research.
  7. Applying quantitative methods, algorithms, and metrics to assess the value and efficiency of intervention strategies.
  8. Identifying appropriate study designs, methods, and measures for interventions that target upstream (e.g., beyond the individual level) risk and/or protective factors for mental illness, including mental health disparities.

Female patient receiving transcranial magnetic stimulation on her brain from male doctor

Clinical trials have traditionally focused on diagnostic status and symptom severity. Inattention to the complex topography of intervention targets, and to individual differences in psychopathology and intervention needs and preferences, can limit the value of findings and their potential uptake in routine practice. Strategies should focus on functional outcomes, considered within the context of an individual’s development stage, environment, and culture.

Personalized mental health interventions mean that people should receive preventive and treatment interventions optimally matched to their needs. Optimizing interventions and technologies will not only require consideration of symptoms, phases of illness, and functioning, but also a broader consideration of genetic, developmental, psychosocial, cultural, and environmental factors, and functional deficits and needs. Optimal care will also require consideration of the characteristics of population stratification or the candidate interventions and characteristics of providers and settings. Efficient research designs are needed to examine approaches for optimizing interventions for individuals, families, communities, populations, and settings.

To better tailor existing interventions to optimize outcomes, NIMH will support research that employs the following Strategies:

Interest areas include:

  1. Investigating heterogeneity in, and mechanisms of, response to existing efficacious preventive and treatment interventions to inform personalized interventions that address specific outcomes.
  2. Investigating strategies for sequencing or integrating interventions that are optimal for individuals in the context of phases of disease progression, stages of development, and other characteristics.
  3. Establishing the safety and efficacy of therapeutic interventions previously found to be effective in one population and applied to other, understudied populations, such as children, older adults, minoritized populations, and women at various phases of the reproductive cycle (including menarche, the menstrual cycle, all stages of pregnancy, and menopause), while testing targets, target engagement, and/or biomarkers of efficacy specific to these populations.
  4. Running prospective studies of known efficacious interventions to identify moderator variables and objective biomarkers, digital phenotypes, composite biomarkers, and/or multi-modality derived biotypes.
  5. Developing multi-modal intervention strategies that combine the simultaneous application of established or novel pharmacological, psychosocial, biologic, and/or neuromodulation interventions to selectively access specific therapeutic targets through synergistic action.

Interest areas include:

  1. Developing and refining research methods that can be used to advance personalized interventions, including computational algorithms for prescriptive approaches and innovative trial designs.
  2. Reanalyzing or conducting meta-analyses using individual or aggregated clinical trials, patient registries, electronic health records, or other existing clinical datasets to identify moderators that might serve as tailoring variables for interventions.
  3. Applying innovative computational approaches (e.g., machine learning, artificial intelligence, pattern classification techniques, predictive analytics) to multiple streams of data (e.g., routinely collected standardized measures in electronic health records, sensor-based data, social media/device use metrics, community-level data) using existing data sources to inform targets and timing for interventions and to facilitate clinical decision-making.
  4. Developing and using innovative trial designs and data collection strategies to test personalized strategies that incorporate tailoring variables (e.g., clinical data, biomarkers, behavioral markers derived from passive sensing of naturalistic behaviors, patient response history) into participant assignment.
  5. Promoting research designs that address the needs of underserved, minoritized, and marginalized groups. Such studies may include computational approaches that address biases in the data used to develop models (e.g., systemic under diagnosis in certain racial or ethnic groups) and use gold standard data that are diverse, appropriately over-sampled for minoritized groups, and that do not train the model to perpetuate existing health disparities.

Effectiveness research aims to generate information about the implementation of interventions and services in real-world settings. Effectiveness research is most useful for informing practice or policy decisions when it addresses a condition that has substantial public health significance; when it justifies the practical benefit of the intervention over existing approaches; when it is conducted in diverse, representative populations and contexts; when interventions are potentially scalable and could be disseminated into current practice; and, when it assesses a broad array of outcomes relevant to interested parties.

Effectiveness research is best implemented through efficient and innovative platforms and designs that advance treatment personalization in community settings. Deployment-focused models of intervention and services research, which consider the key characteristics of the settings and providers where interventions and services will be implemented, are critical. Consistent with the NIMH experimental therapeutics approach to intervention development and testing, there is a need for effectiveness trials that contribute to our overall understanding of intervention change mechanisms. Not only are these effectiveness trials beneficial when they test the impact of interventions on clinical endpoints; they are beneficial when they explicitly examine whether the intervention engages the targets that mediate the clinical benefit.

To better test intervention effectiveness in community practice settings, NIMH will support research that employs the following Strategies:

Interest areas include:

  1. Developing and testing approaches for implementing new indications and developing and testing adaptations or augmentations of evidence-based interventions when research suggests that a moderator or negative prognostic factor can be targeted to improve response substantially for a readily identifiable refractory subgroup.
  2. Testing integrated and sequenced approaches to optimize effectiveness and safety, while minimizing unnecessary or off-label use of devices or psychotropic medications among children, adolescents, and adults.
  3. Developing and testing broadly relevant preventive/early interventions that target shared modifiable risk and protective factors and/or key domains of functioning (e.g., emotion regulation, cognitive systems, social processes) and thereby change life trajectories and reduce risk for multiple mental illnesses.
  4. Focusing on strategies that address the needs of individuals and populations at risk for relapse/recurrence and manage chronic disorders (e.g., post-acute phase interventions/service strategies that are matched to the stage of illness both in terms of the goals and approaches to maximize the chances of complete recovery and sustained remission).
  5. Developing and testing approaches that employ mobile health (mHealth) and other emerging technologies to boost the effectiveness of evidence-based interventions and to monitor health.
  6. Examining when and how social determinants of health moderate intervention outcomes and identifying opportunities to implement interventions that target modifiable determinants.
  7. Using community-engaged research approaches to ensure that mental health interventions align with the needs of underserved, minoritized, and marginalized populations; that community members are involved in all phases of research; and, that community-based intervention studies employ rigorous designs to address health disparities questions.

Interest areas include:

  1. Conducting effectiveness trials that leverage practice-based research and other research investments to inform intervention development and increase the efficiency and relevance of effectiveness research, including identifying targets and optimal timing for intervention.
  2. Supporting refinement of preventive and treatment interventions for mental illnesses, while capitalizing on efficiencies to facilitate participant recruitment and data collection.
  3. Supporting practice-based research aimed at refining and testing efficacious preventive interventions (including universal, selective, indicated, and tiered approaches), so that they are scalable and can be sustainably implemented in settings (e.g., primary care, schools, communities) where preventive services are delivered to youth.
  4. Externally validating practice-based research across diverse populations and contexts to enhance the relevance and translation potential of trial results.

Interest areas include:

  1. Encouraging deployment-focused intervention and service models and effectiveness testing that consider the perspective of relevant interested parties and key characteristics of intended intervention settings, to increase the likelihood that the interventions/services are feasible and scalable, and the research results will have utility for end users.
  2. Emphasizing hybrid effectiveness-implementation research that goes beyond examining the effect of interventions on symptomatic or functional outcomes and designing studies to address questions regarding how client-, provider-, community-, and organizational-level factors impact clinical outcomes, implementation, and scalability of research-generated interventions.
  3. Encouraging hybrid effectiveness-implementation trials across diverse settings to identify setting characteristics (e.g., workforce capacity, case mix) that impact intervention delivery and test strategies to sustain intervention effectiveness and quality of implementation in diverse settings.
  4. Examining novel applications of technology that can generalize across indications, target populations, and operating platforms to facilitate the delivery of interventions and enhance their reach and therapeutic value.

 

Progress for Goal 3

Highlighting efforts to improve preventive and therapeutic interventions.

Updated: