R01MH125179

Enhancing Engagement with Digital Mental Health Care

Abstract

Digital Mental Health (DMH) is the use of technology to improve population well-being through rapid disease detection, outcome measurement, and care [1]. Although several randomized clinical trials have demonstrated that digital mental health tools are highly effective [2-6], most consumers do not sustain their use of these tools [7-9]. The field currently lacks an understanding of DMH tool engagement, how engagement is associated with well-being, and what practices are effective at sustaining engagement.

In this partnership between Mental Health America (MHA), Talkspace (TS), and the University of Washington (UW), we propose a naturalistic and experimental, theory-driven program [10,11] of research, with the aim of understanding:

1) How consumer engagement in self-help and clinician-assisted DMH varies and what engagement patterns exist,
2) The association between patterns of engagement and important consumer outcomes, and
3) The effectiveness of personalized strategies for optimal engagement with DMH treatment.

This study will prospectively follow a large, naturalistic sample of MHA and TS consumers and will apply machine learning, user-centered design strategies, and micro-randomized and sequential multiple assignment randomized (SMART) trials to address these aims.

As is usual practice for both platforms, consumers will complete online mental health screening and assessment, and we will be able to classify participants by disease status and symptom severity. The sample we will be working with will not be limited by diagnosis or co-morbidities. Participants will be 10 years old and older and enter the MHA and TS platforms prospectively over 4 years.

In order to test the first aim, we will identify a minimum of 100,000 consumers who have accessed MHA and TS platforms in the past. Participant data will be analyzed statistically to reveal differences in engagement and dropout across groups based on demographics, symptoms, and platform activity.

For aim 2, we will use supervised machine learning techniques to identify subtypes based on consumer demographics, engagement patterns with DMH, reasons for disengagement, success of existing MHA and TS engagement strategies, and satisfaction with the DMH tools that are predictive of future engagement patterns.

Finally, based on the outcomes from aim 2, in aim 3 we will conduct focus groups applying user-centered design strategies to identify and co-build potentially effective engagement strategies for particular client subtypes. We will then conduct a series of micro-randomized and SMART trials to determine which theory-driven engagement strategies, co-designed with users, have the greatest fit with subtypes developed under aim 2. We will test the effectiveness of these strategies to:

1) Prevent disengagement from those who are more likely to have poor outcomes after disengagement,
2) Improve movement from motivation to volition, and
3) Enhance optimal dose of DMH engagement and consequently improve mental health outcomes.

These data will be analyzed using longitudinal mixed effects models with effect coding to estimate the effectiveness of each strategy on client engagement behavior and mental health outcomes.

University Of Washington

THE MISSION OF THE NATIONAL INSTITUTE OF MENTAL HEALTH (NIMH) IS TO TRANSFORM THE UNDERSTANDING AND TREATMENT OF MENTAL ILLNESSES THROUGH BASIC AND CLINICAL RESEARCH, PAVING THE WAY FOR PREVENTION, RECOVERY, AND CURE. IN MAY 2020, NIMH RELEASED ITS NEW STRATEGIC PLAN FOR RESEARCH. THE NEW STRATEGIC PLAN BUILDS ON THE SUCCESSES OF PREVIOUS NIMH STRATEGIC PLANS BY PROVIDING A FRAMEWORK FOR SCIENTIFIC RESEARCH AND EXPLORATION, AND ADDRESSING NEW CHALLENGES IN MENTAL HEALTH. THE NEW STRATEGIC PLAN OUTLINES FOUR HIGH-LEVEL GOALS: GOAL 1: DEFINE THE BRAIN MECHANISMS UNDERLYING COMPLEX BEHAVIORS GOAL 2: EXAMINE MENTAL ILLNESS TRAJECTORIES ACROSS THE LIFESPAN GOAL 3: STRIVE FOR PREVENTION AND CURES GOAL 4: STRENGTHEN THE PUBLIC HEALTH IMPACT OF NIMH-SUPPORTED RESEARCH THESE FOUR GOALS FORM A BROAD ROADMAP FOR THE INSTITUTE'S RESEARCH PRIORITIES OVER THE NEXT FIVE YEARS, BEGINNING WITH THE FUNDAMENTAL SCIENCE OF THE BRAIN AND BEHAVIOR, AND EXTENDING THROUGH EVIDENCE-BASED SERVICES THAT IMPROVE PUBLIC HEALTH OUTCOMES. THE INSTITUTE'S OVERALL FUNDING STRATEGY IS TO SUPPORT A BROAD SPECTRUM OF INVESTIGATOR-INITIATED RESEARCH IN FUNDAMENTAL SCIENCE, WITH INCREASING USE OF INSTITUTE-SOLICITED INITIATIVES FOR APPLIED RESEARCH WHERE PUBLIC HEALTH IMPACT IS A SHORT-TERM MEASURE OF SUCCESS. THE NEW STRATEGIC PLAN ALSO ADDRESSES A NUMBER OF CROSS-CUTTING THEMES THAT ARE RELEVANT TO ALL RESEARCH SUPPORTED BY NIMH, THESE THEMES HIGHLIGHT AREAS WHERE NIMH-FUNDED SCIENCE MAY HAVE THE GREATEST IMPACT, BRIDGE GAPS, AND OFFER NOVEL APPROACHES TO ACCELERATE ADVANCES IN MENTAL HEALTH RESEARCH. FOR EXAMPLE, NIMH VALUES A COMPREHENSIVE RESEARCH AGENDA THAT TAKES AN INCLUSIVE APPROACH THAT ENSURES RESEARCH INTERESTS ARE VARIED, MAINTAIN DIVERSE PARTICIPATION AND PARTNERSHIPS, AND ACHIEVE RESEARCH GOALS ACROSS MULTIPLE TIMEFRAMES. THIS INCLUDES DIVERSE METHODOLOGIES, TOOLS, AND MODELS, RESEARCH ADDRESSING COMPLEX BASIC, TRANSLATIONAL, AND APPLIED QUESTIONS, RESEARCH INCLUDING BOTH SEXES AND, AS APPROPRIATE, GENETIC BACKGROUND, AND, PARTICIPANTS FROM DIVERSE RACIAL AND ETHNIC BACKGROUNDS, AND ACROSS GENDER IDENTITIES, GEOGRAPHICAL CONTEXT, SOCIOECONOMIC STATUS, NEUROTYPE, AND AGE OFFERING THE BEST POSSIBLE REPRESENTATION, FOR THE BROADEST NUMBER OF INDIVIDUALS WHO MAY ULTIMATELY BENEFIT FROM THESE SCIENTIFIC ADVANCES. TO ACCOMPLISH THE GOALS OUTLINED IN THE NEW STRATEGIC PLAN, NIMH WILL SUPPORT RESEARCH THAT AIMS: TO CHARACTERIZE THE GENOMIC, MOLECULAR, CELLULAR, AND CIRCUIT COMPONENTS CONTRIBUTING TO BRAIN ORGANIZATION AND FUNCTION, TO IDENTIFY THE DEVELOPMENTAL, FUNCTIONAL, AND REGULATORY MECHANISMS RELEVANT TO COGNITIVE, AFFECTIVE, AND SOCIAL DOMAINS, ACROSS UNITS OF ANALYSIS, AND, TO GENERATE AND VALIDATE NOVEL TOOLS, TECHNIQUES, AND MEASURES TO QUANTIFY CHANGES IN THE ACTIVITY OF MOLECULES, CELLS, CIRCUITS, AND CONNECTOMES. TO DISCOVER GENE VARIANTS AND OTHER GENOMIC ELEMENTS THAT CONTRIBUTE TO THE DEVELOPMENT OF MENTAL ILLNESSES IN DIVERSE POPULATIONS, TO ADVANCE OUR UNDERSTANDING OF THE COMPLEX ETIOLOGY OF MENTAL ILLNESSES USING MOLECULAR EPIDEMIOLOGIC APPROACHES THAT INCORPORATE INDIVIDUAL GENETIC INFORMATION IN LARGE COHORTS, TO ELUCIDATE HOW HUMAN GENETIC VARIATION AFFECTS THE COORDINATION OF MOLECULAR, CELLULAR, AND PHYSIOLOGICAL NETWORKS SUPPORTING HIGHER-ORDER FUNCTIONS AND EMERGENT PROPERTIES OF NEUROBIOLOGICAL SYSTEMS, AND, TO DEVELOP NOVEL TOOLS AND TECHNIQUES FOR THE ANALYSIS OF LARGE-SCALE GENETIC, MULTI-OMIC DATA AS IT APPLIES TO MENTAL HEALTH. TO UTILIZE CONNECTOMIC APPROACHES TO IDENTIFY BRAIN NETWORKS AND CIRCUIT COMPONENTS THAT CONTRIBUTE TO VARIOUS ASPECTS OF MENTAL FUNCTION AND DYSFUNCTION, TO DETERMINE THROUGH BRAIN-WIDE ANALYSIS HOW CHANGES IN THE PHYSIOLOGICAL PROPERTIES OF MOLECULES, CELLS, AND CIRCUITS CONTRIBUTE TO MENTAL ILLNESSES, TO DEVELOP MOLECULAR, CELLULAR, AND CIRCUIT-LEVEL BIOMARKERS OF IMPAIRED NEURAL FUNCTION IN HUMANS, AND, TO DEVELOP INNOVATIVE TECHNOLOGIES, INCLUDING NEW IMAGING, COMPUTATIONAL, PHARMACOLOGICAL, AND GENETIC TOOLS TO INTERROGATE AND MODULATE CIRCUIT ACTIVITY AND STRUCTURE ALTERED IN MENTAL ILLNESSES. TO ELUCIDATE THE MECHANISMS CONTRIBUTING TO THE TRAJECTORIES OF BRAIN DEVELOPMENT AND BEHAVIOR, AND, TO CHARACTERIZE THE EMERGENCE AND PROGRESSION OF MENTAL ILLNESSES, AND IDENTIFYING SENSITIVE PERIODS FOR OPTIMAL INTERVENTION. TO DETERMINE EARLY RISK AND PROTECTIVE FACTORS, AND RELATED MECHANISMS, TO SERVE AS NOVEL INTERVENTION GROUPS, AND, TO DEVELOP RELIABLE AND ROBUST BIOMARKERS AND ASSESSMENT TOOLS TO PREDICT ILLNESS ONSET, COURSE, AND ACROSS DIVERSE POPULATIONS. TO DEVELOP NOVEL INTERVENTIONS USING A MECHANISM-INFORMED, EXPERIMENTAL THERAPEUTICS APPROACH, AND, TO DEVELOP AND IMPLEMENT MEASUREMENT STRATEGIES TO FACILITATE MECHANISM-BASED INTERVENTION DEVELOPMENT AND TESTING. TO INVESTIGATE PERSONALIZED INTERVENTION STRATEGIES ACROSS DISEASE PROGRESSION AND DEVELOPMENT, AND, TO DEVELOP AND REFINE COMPUTATIONAL APPROACHES AND RESEARCH DESIGNS THAT CAN BE USED TO INFORM AND TEST PERSONALIZED INTERVENTIONS. TO DEVELOP AND TEST APPROACHES FOR ADAPTING, COMBINING, AND SEQUENCING INTERVENTIONS TO ACHIEVE THE GREATEST IMPACT ON THE LIVES AND FUNCTIONING OF PERSONS SEEKING CARE, TO CONDUCT EFFICIENT PRAGMATIC TRIALS THAT EMPLOY NEW TOOLS TO RAPIDLY IDENTIFY, ENGAGE, ASSESS, AND FOLLOW PARTICIPANTS IN THE CONTEXT OF ROUTINE CARE, AND, TO ENHANCE THE PRACTICAL RELEVANCE OF EFFECTIVENESS RESEARCH VIA DEPLOYMENT-FOCUSED, HYBRID, EFFECTIVENESS-IMPLEMENTATION STUDIES. TO EMPLOY ASSESSMENT PLATFORMS WITHIN HEALTHCARE SYSTEMS TO ACCURATELY ASSESS THE DISTRIBUTION AND DETERMINANTS OF MENTAL ILLNESSES AND TO INFORM STRATEGIES FOR IMPROVED SERVICES, TO OPTIMIZE REAL-WORLD DATA COLLECTION SYSTEMS TO IDENTIFY STRATEGIES FOR IMPROVING ACCESS, QUALITY, EFFECTIVENESS, AND CONTINUITY OF MENTAL HEALTH SERVICES, AND, TO COMPARE ALTERNATIVE FINANCING MODELS TO PROMOTE EFFECTIVE AND EFFICIENT CARE FOR INDIVIDUALS WITH SERIOUS EMOTIONAL DISTURBANCES AND SERIOUS MENTAL ILLNESSES. TO STRENGTHEN PARTNERSHIPS WITH KEY STAKEHOLDERS TO DEVELOP AND VALIDATE STRATEGIES FOR IMPLEMENTING, SUSTAINING, AND CONTINUOUSLY IMPROVE EVIDENCE-BASED PRACTICES, TO BUILD MODELS TO SCALE-UP EVIDENCE-BASED PRACTICES FOR USE IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE AND OTHER SETTINGS, AND, TO DEVELOP DECISION-SUPPORT TOOLS AND TECHNOLOGIES THAT INCREASE THE EFFECTIVENESS AND CONTINUOUS IMPROVEMENT OF MENTAL HEALTH INTERVENTIONS IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE, AND OTHER SETTINGS. TO ADAPT, VALIDATE, AND SCALE-UP PROGRAMS CURRENTLY IN USE THAT IMPROVE MENTAL HEALTH SERVICES FOR UNDERSERVED POPULATIONS, TO DEVELOP AND VALIDATE SERVICE DELIVERY MODELS THAT PROVIDE EVIDENCE-BASED CARE FOR INDIVIDUALS THROUGHOUT THE COURSE OF MENTAL ILLNESS, TO DEVELOP AND VALIDATE SYSTEMS-LEVEL STRATEGIES USING TECHNOLOGY AND OTHER APPROACHES, TO IDENTIFY, SUPPORT, AND MONITOR THE EFFECTIVENESS OF EVIDENCE-BASED CARE THROUGHOUT THE COURSE OF ILLNESS, AND, TO DEVELOP AND VALIDATE DECISION-MAKING MODELS THAT BRIDGE MENTAL HEALTH, MEDICAL, AND OTHER CARE SETTINGS TO INTEGRATE THE APPROPRIATE CARE FOR PEOPLE WITH SERIOUS MENTAL ILLNESSES AND COMORBID MEDICAL CONDITIONS.

93.242 - Mental Health Research Grants

National Institute of Mental Health (NIMH) [HHS - NIH]

Seattle, Washington 98195 United States

Single Zip Code

Laboratories to Optimize Digital Health (R01 Clinical Trial Required) (RFA-MH-20-510)

Amendment Since initial award the End Date has been extended from 11/30/24 to 11/30/25 and the total obligations have increased 262% from $872,555 to $3,161,673.