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DATAcc by DiMe releases first set of digital measures built specifically for common mental health disorders

The Digital Health Measurement Collaborative Community (DATAcc) by the Digital Medicine Society (DiMe) is a collaborative community with the FDA’s Center for Devices and Radiological Health (CDRH). We provide a forum for collaboration where partners and experts from across the digital health field work to advance the use of digital health measures in research to improve lives.

News provided by

Digital Medicine Society (DiMe)

Jun 04, 2026, 10:45 ET

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Developed with 20+ partners across industry, advocacy, and research, the resources give drug developers, regulators, payors, and clinicians a shared foundation for measuring symptoms and treatment effects

BOSTON, June 4, 2026 /PRNewswire/ -- The Digital Health Measurement Collaborative Community (DATAcc) by the Digital Medicine Society (DiMe) today released the Digital Measures Set for Common Mental Health Disorders, the first set of digital measures built specifically for common mental health disorders.

Mental health disorders affect roughly one in seven people, yet most common mental health conditions remain defined by broad diagnostic categories that encompass people with very different symptoms, experiences, and treatment responses. Existing treatments, including widely used therapies such as SSRIs, help many patients, but predicting who will benefit from which intervention remains challenging.

Clinical trials have long relied on intermittent assessments administered at scheduled visits, limiting the field's ability to recognize how symptoms fluctuate over time and in different contexts. As a result, researchers, clinicians, and patients often lack the tools needed to identify meaningful disease subtypes, understand treatment response with greater precision, and determine which interventions are most likely to benefit a particular individual.

Sensor-generated measures offer a path forward. Measures such as sleep regularity, movement, cognitive performance, heart rate variability, speech biomarkers, and facial and gaze features can provide objective, longitudinal insight into how people with common mental health disorders function in daily life. Together, they create new opportunities to identify clinically meaningful patterns across broad diagnostic categories, support more precise treatment development and selection, and evaluate outcomes in ways that better reflect patients' lived experience.

The implications extend far beyond clinical trials. CMS's ACCESS Model extends value-based payment into behavioral health, a shift that DiMe has championed. Yet many of the measures currently available to assess performance remained rooted in episodic assessments that provide only limited visibility into how patients are doing between visits. As healthcare increasingly moves toward outcomes-based payment - and new medical products seek to differentiate themselves for pricing and prescribing, the field needs more reliable and relevant ways to understand whether patients are actually improving.

A similar challenge is impacting how the field evaluates AI-enabled mental health tools. The FDA's Digital Health Advisory Committee meeting in November 2025 on generative AI in mental health devices, and the AMA's recent warning to Congress to use stronger safeguards on AI chatbots in mental health care, surface the same concern: AI tools are scaling far ahead of the field's ability to evaluate whether they help, harm, or have no effect. This set of digital measures gives developers, regulators, payers, virtual-first care providers, and clinicians a shared, evidence-based foundation for measuring what matters in mental health, grounded in real patient experience.

"Advancing digital endpoints in mental health to date has been slow, careful work, and the field has done it without a shared foundation to build from," said Jennifer Goldsack, CEO of DiMe. "These measures help us move beyond asking whether a treatment works on average and toward understanding who it works for, under what circumstances, and how improvement shows up in daily life. They create an opportunity to identify clinically meaningful patterns across broad diagnostic categories, support more precise treatment development and selection, and give the field a common framework for evaluating outcomes that matter to patients."

DATAcc by DiMe's Digital Measures Set for Common Mental Health Disorders includes seven measures mapped to specific concepts of interest, capturing what digital health technologies can reliably measure in daily life, including sleep, physical activity, variability in daily routines, cognitive function, changes in speech and language, autonomic function, and facial and gaze features. The set also identifies concepts of interest for which no measure is yet recommended, signaling where the next generation of products is needed.

The resources translate the measures into practice for common mental health disorders:

  • These digital measures, used as endpoints in clinical trials, help sponsors and research teams use measures such as sleep, activity, and autonomic function as exploratory, secondary, or, in select cases, primary endpoints, with practical implementation advice on evidence, analysis, and trial design.
  • Exploring these digital measures for phenotyping in clinical trials shows how to use the measures to build digital phenotypes that move beyond disease-based models, supporting more precise subtyping and population enrichment in both pre- and post-market work.
  • Applying the digital measures set to support value-based care highlights their potential to complement clinical judgment in longitudinal care and to support value-based reimbursement models, with partner case studies showing how care teams use these measures to monitor patients between visits and to inform clinical and program decisions.

Built on DATAcc by DiMe's prior work to advance the use of sensor-based digital health technologies (sDHTs) for mental health research and clinical practice, commissioned by Wellcome, this digital measures set reflects growing recognition that common mental health disorders are dynamic, heterogeneous conditions that cannot be fully understood through episodic assessments alone. By enabling continuous measurement of factors such as sleep, activity, cognition, speech, and physiological response, these measures can help researchers and clinicians better characterize patients, identify meaningful phenotypes, evaluate treatment effectiveness in real-world settings, and support the transition toward outcomes-based approaches in both mental and physical healthcare. They also create opportunities to reduce trial burden, improve development efficiency, and ultimately improve patient outcomes.

"Millions of people now access mental health care through digital channels, which means the field has both the responsibility and the opportunity to measure what works with far greater precision than traditional care has allowed," said Dr. Russell DuBois, Vice President of Clinical Quality, Operations and Innovation, BetterHelp. "A set of digital measures grounded in patient experience gives providers, researchers, and developers a common language for understanding how people are doing in their daily lives, not just in scheduled assessments. That is how the field moves toward care that is more responsive, more personalized, and more effective at scale."

The release advances DiMe's Healthcare 2030 vision for a sustainable health system in the digital era, and builds on DATAcc by DiMe's broader Library of Digital Measurement Products, which catalogs validated digital measures across sleep, Alzheimer's disease and related dementias, physical activity, and Parkinson's disease.

DiMe is proud to have developed the Digital Measures Set for Common Mental Health Disorders with: American Psychological Association, Aura, BetterHelp, BlueSkeye AI, Callyope, Compass Pathways, Cumulus Neuroscience, Empatica, Emteq Labs, FDA, Feel Therapeutics, Foundation for the National Institutes of Health (FNIH), Headlamp Health, Healthesphere, Kids Research Institute Australia, Ksana Health, Lightfully, Linus Health, Massachusetts General Hospital, Mental Health America, MindMed, Neurocrine, Otsuka, PATHS, Purdue University Weldon School of Biomedical Engineering, Talkspace, Thymia, TMF Health Quality Institute, UCLA Grand Challenge, Videra Health, and Wake Forest.

About DATAcc by DiMe
The Digital Health Measurement Collaborative Community (DATAcc) by the Digital Medicine Society (DiMe) is a collaborative community with the FDA's Center for Devices and Radiological Health. DATAcc provides a forum where partners and experts from across the digital health field advance the use of digital health measures in research and care to improve lives.

About the Digital Medicine Society (DiMe)
The Digital Medicine Society (DiMe) is a global nonprofit organization dedicated to advancing the safe, effective, equitable, and ethical use of digital technologies to redefine healthcare and improve lives. DiMe delivers open-access resources, multi-stakeholder collaborations, and evidence-based frameworks to accelerate the responsible digitization of healthcare.
Media contact:
[email protected]

SOURCE Digital Medicine Society (DiMe)

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