Notice of Information: NIMH High-Priority Areas for Research on Digital Health Technology to Advance Assessment, Detection, Prevention, Treatment, and Delivery of Services for Mental Health Conditions

Notice Number: NOT-MH-18-031

Key Dates
Release Date: April 12, 2018

Related Announcements

Issued by
National Institute of Mental Health (NIMH)


NIMH is issuing this Notice to highlight its interest in receiving grant applications that utilize digital health technology to advance assessment, detection, prevention, treatment, and delivery of services for mental health conditions.
Digital health incorporates mobile health (mHealth) and health information technology (smartphones, wearable sensors, internet platforms, and electronic health records) with biological, social, and behavioral data. Digital health technology offers unprecedented opportunities to help consumers, clinicians, and researchers measure, manage, and improve health and productivity. These tools also have the potential to improve our understanding of mental illness, to track the course of illnesses and recovery, and to provide and enhance mental health care.
Well-designed research is necessary to evaluate the efficacy/effectiveness of digital health technology to increase the reach, efficiency, effectiveness, and quality of interventions and services to populations in need. Research is needed to optimize existing technology and to develop new approaches to understand the life course and etiology of mental disorders and to predict and prevent mental illness.  The NIMH is interested in research applications that leverage technology to efficiently screen, accurately diagnose and rapidly treat mental illness.  The NIMH is also interested in strategies designed to leverage existing digital health platforms to enable the rapid enrollment of participants who are representative of the population and nimble intervention refinement during the course of the research.
To inform research in this area, the NIMH National Advisory Mental Health Council (NAMHC) recently convened a Workgroup on Behavioral and Social Science Research to explore opportunities and challenges of using new information technologies to study human behaviors relevant to the NIMH mission.  The workgroup report provides an overview of NIMH research priorities, aligns these priorities with the NIMH Strategic Plan and highlights key areas of opportunity and recommendations related to key digital health topic areas.
The NIMH is interested in research that will support development, refinement, and implementation of evidence-supported digital health technology into routine practice. Research strategies might include case-control, cross-sectional, and longitudinal designs as well as randomized controlled trials, quasi-experimental designs with non-randomized comparison groups, time series designs, and other designs of equivalent rigor and relevance.  
Applicants are encouraged to review the NIMH Council Workgroup report that summarizes the state of the science, research priorities, and potential research pathways. Where appropriate, applicants are encouraged to utilize existing hardware/software as well as data from existing commercial and open source digital health applications and online platforms. Researchers are also encouraged to consider collaborations with engineers, data scientists, health system experts, technology designers as well as end users (consumers, clinicians administrators).
Examples of applications that NIMH identifies as high priority include  , but are not limited to, studies that are consistent with recommendations in the NAMHC Workgroup Report and address the following areas: 
Assessment--Technology-assisted data collection presents opportunities for real-time assessment (e.g., experience sampling) and automated collection of behavior in natural environments (e.g., via sensors for ambient monitoring, natural language processing for extraction from medical records or other recorded/written sources).  Related research might include studies that combine data collected through technology-assisted approaches with data from other sources (e.g., clinical history, family history, cognitive testing) to create digital/behavioral phenotypes to:

  • develop and test sensors that can be used to accurately infer subjective mental states (e.g. mood states, heightened risk for self-harm, cognitive/thought processes, abnormal perceptions) from objectively observable behaviors (e.g. voice/speech samples, facial movement, locomotion, GPS, social sensing, device/electronic media use patterns). 
  • test predictive models capable of identifying individual patterns of risk or dysfunction both within individuals (over time) and across individuals (finding similar clusters of predictors across a group).
  • use novel technology to collect and analyze real-time data to characterize dimensions of functioning (e.g. RDOC) and complex behaviors (e.g. social perception) among typical and patient populations.
  • understand developmental trajectories and illness course; collect passive, real-time data from people who are well, yet at risk for mental illness, across locations and age groups, to understand and identify markers and patterns associated with normal and aberrant developmental processes (i.e., to better characterize risk trajectories across development, including indicators early in life and before symptoms are manifest).
  • develop analytic/computational approaches to fuse high dimensionality data derived from mobile sensors with simultaneously recorded biological/physiology data to discover brain-behavior relationships in real life settings.
  • examine and predict illness course/trajectories, including research aimed at identifying at-risk individuals for early intervention/prevention and or monitoring course and pre-empting deterioration in the context of self-management or clinician-moderated monitoring.
  • test and validate sensor-based or other technology-assisted approaches to measuring response to therapeutic interventions, including research that examines psychometric properties, sensitivity to change and correspondence with conventional clinical assessments.
Intervention Refinement and Testing--New information technologies might also be used to enhance the reach or boost the therapeutic value of interventions across a variety of conditions and illness phases. Technology-assisted approaches include primarily self-administered, stand-alone interventions (e.g., for population-level, health promotion/prevention) as well as clinician-supported delivery. 
Studies that use mobile and other emerging technologies to intervene might include those test approaches that leverage technology to:
  • identify and promote more prescriptive therapeutics (e.g., use of machine learning or other approaches to rapidly refine intervention content, match individuals to research-informed approaches, develop and implement algorithms within electronic health records to drive workflow; use of technology-assisted intervention delivery as part of a stepped-care approach).
  • develop, test, and deliver adaptive interventions and just-in-time interventions that can be ‘pushed out’ via mobile technology based on information regarding the individual’s current state.
  • optimize the benefit of in-person treatment using mobile technology to bridge therapy sessions and promote between-session skill practice/acquisition.
  • examine the utility of technology-facilitated interventions as part of a measurement-based approach to care that optimizes the delivery of high value treatment options depending on responses and individual needs.
  • deliver interventions designed to overcome well-documented adherence challenges with self-administered interventions (e.g., using game-like format or other research-informed approaches to enhance motivation and promote continued engagement).
  • leverage emerging platforms, such as social media platforms for intervening.
  • conduct more nimble intervention refinement and testing (e.g., using web-based platforms to launch trials, rapidly identify and enroll participants, and parametrically refine intervention content, dose, and delivery parameters to optimize the intervention’s therapeutic benefit and efficiency.
Service Interventions and Service Delivery--Technology might also be harnessed to facilitate service delivery via patient-facing, clinician-facing, or systems-level applications that are designed to demonstrably improve service access, engagement/continuity, quality, efficiency, equity, and value.  Services-related applications might include technology studies designed to:
  • Develop and test strategies that can be used to support providers in their use of measurement-based care, including strategies to facilitate system-level quality monitoring and improve workflows (e.g., use of technology, including automated, passive assessment, to extract quality metrics from patient encounters or from EHR data).
  • Develop and test quality improvement strategies, including approaches to promote the use of research-informed strategies (e.g., studies to develop and test technology-supported decision aids; studies to evaluate the utility of prompts or aids to facilitate implementation of research-supported treatment algorithms or implementation of evidence-based psychosocial interventions).
  • Identify and develop new factors that impact the ultimate adoption of technology including research to study dissemination and implementation strategies within large healthcare systems and existing online delivery platforms.
  • Develop and test technology-driven approaches to improve access to and promote engagement with and continuity of care during known periods of heightened risk, such as care transitions between systems (e.g., handoffs between emergency departments and inpatient psychiatric or substance abuse treatment; transitions between outpatient mental health/substance abuse programs and primary care settings).
  • Develop and test patient and/or clinician-facing applications or “dashboards” that apply scientific principles to demonstrably facilitate monitoring, illness management (e.g., adherence promotion), and early detection of changes in patient status that might signal the need for additional or more intensive services.
  • Evaluate patterns of use and examine the utility of existing mental health apps to inform the development and testing of tools to facilitate consumer decision making.

Across these topic areas (assessment, intervention refinement/testing, and service delivery), NIMH encourages applications that test generalizable principles or approaches to using technology to improve the accuracy and efficiency of assessment and the effectiveness and quality of intervention and service delivery. NIMH also encourages research attention to known challenges with uptake and adherence/sustained use of technology-based approaches and attention to privacy and other safety/ethical considerations associated with the use of technology for research and clinical purposes, as detailed in the NAMHC Workgroup Report. In contrast, proposals to test specific products or translate existing measures/interventions onto new technology platforms are not encouraged. 

Examples of studies that would not be considered high priority  include the following:

Applications that convert established face-to-face interventions to a technology based intervention.
Interventions that consist of solely one-way text messages or reminders.

Applications that take interventions developed for adults and propose to test them among youth without taking into account developmental differences.

Funding Opportunity Announcements that can be used to pursue research in these high priority areas are summarized below.

For applications proposing non-interventional studies focused on technology-assisted approaches to assessment (e.g., assessment of risk/etiological factors or course), potential FOAs include:

  • PA-18-350 (R21 Exploratory/Development Research Grant - Clinical Trial Not Allowed)
  • PAR-18-242 (R21 Mobile Health: Technology and Outcomes in Low and Middle Income Countries – Clinical Trial Optional)
  • PA-18-484 (R01 NIH Research Project Grant - Clinical Trial Not Allowed)
  • PAR-18-267  (R34 Pilot Services Research Grants Not Involving Interventions)
  • PAR-17-264 (R01 Innovative Mental Health Service Research Not Involving Clinical Trials)
  • PA-18-338 (R01 Revision Applications for Validation of Mobile/Wireless Health Tools for Measurement and Intervention)
For applications proposing to develop and test technology-facilitated preventive, therapeutic, and service interventions, potential FOAs include:
Development of Psychosocial Therapeutic and Preventive Interventions for Mental Disorders
  • PAR-18-242 (R21 Mobile Health: Technology and Outcomes in Low and Middle-Income Countries – Clinical Trial Optional)
Pilot Effectiveness Trials
  • RFA-MH-18-706 (R34 - Pilot Effectiveness Trials for Treatment, Preventive and Services Interventions - Clinical Trial Required)
  • PAR-18-431 (R34 Pilot Effectiveness Trials for Post-Acute Interventions and Services to Optimize Longer-term Outcomes - Clinical Trial Required)
Confirmatory Efficacy Clinical Trials of Non-Pharmacological Interventions for Mental Disorders  
Clinical Trials to Test the Effectiveness of Treatment, Preventive, and Services Interventions
These FOAs aim to support clinical trials to establish the effectiveness of interventions and to test hypotheses regarding moderators, mediators, and mechanisms of action of these interventions. These FOAs support clinical trials designed to test the therapeutic value of treatment and preventive interventions for which there is already evidence of efficacy, for use in community and practice settings. This FOA also supports clinical trials to test patient-, provider-, organizational-, or systems -level services interventions to improve service access, continuity, quality, equity, and/or value of services. The intervention research covered under this announcement is explicitly focused on practice-relevant questions.  
  • RFA-MH-18-701 (R01 – Clinical Trial Required)
  • RFA-MH-18-700 (Collaborative R01 – Clinical Trial Required)
  • PAR-18-430 (R01) (R01 - Effectiveness Trials for Post-Acute Interventions and Services to Optimize Longer-term Outcomes - Clinical Trial Required)
Small Business Innovation Research and Small Business Technology Transfer Grant Applications SBIR/STTR
  • PA-18-574  (R43/R44 Small Business Innovation Research Grant Applications - Clinical Trial Not Allowed)
  • PA-18-575 (R41/R42 Small Business Technology Transfer Grant Applications - Clinical Trial Not Allowed)
  • PA-18-579 (R41/R42 – STTR Complex Technologies and Therapeutics Development for Mental Health Research and Practice -Clinical Trial Optional)
  • PA-18-566 (R43/R44 - SBIR Complex Technologies and Therapeutics Development for Mental Health Research and Practice - Clinical Trial Optional)
  • PA-18-573  (R43/R44 Small Business Innovation Research Grant Applications - Clinical Trial Required)
  • PA-18-576 (R41/R42 Small Business Technology Transfer Grant Applications - Clinical Trial Required)
Please note that investigators interested in pursuing clinical trial research should review the NIMH Clinical Trials Funding Opportunity Announcements  website:
Applicants considering such an application are strongly encouraged to consult with NIMH Program Officials as early in advance as possible prior to submission.


Please direct all inquiries to:

Adam Haim, Ph.D.
National Institute of Mental Health (NIMH)
Telephone: 301-435-3593