Criteria
Helping You Choose with Confidence
The APA Labs Digital Badge program reviews digital mental and behavioral health tools across six critical domains that reflect key areas of importance in mental health care and digital health delivery. This comprehensive evaluation approach - which includes rigorous risk identification and assessment of AI components – supports informed decision-making for both clinicians and users seeking mental and behavioral health support.
6 Critical Domains
Scene Setters
Scientific Principles
Regulation & Safety
Data Protection & Privacy
Technical Security & Stability
Usability & Accessibility
AI Evaluation Framework
Our approach to evaluating AI products and components is product-specific - the risks present in any given product depend substantially on the type of AI used and what it is asked to do, and the evaluation reflects this.
Domain 1: Scene Setters
The Scene Setters domain offers a deeper, more tailored front-end assessment for psychological and behavioral products. It separates out key scoping elements — including product purpose, mental health focus, target population, AI use, and funding model — to ensure clarity before detailed scoring begins.
Scene Setters includes special emphasis on:
Target audiences of products
Inclusivity and underserved populations
Clinical framing of product functions in the context of behavioral health
Expanded AI functionality criteria and ethical AI use
This domain sets a strong foundation for downstream assessment, making it easier to determine scope, risk, and relevance to APA’s standards.
Criteria Categories
Mental Health Relevance & Intended Use
Target Population & Priority Groups
Data Collection & Sharing Overview
Use of Algorithms & AI
Device Claims or Classifications
Communication Modes & User Interaction
Funding Model & Claimed Benefits
Domain 2: Scientific Principles
The Scientific Principles domain captures a nuanced and clinically relevant understanding of evidence quality, setting, and impact — particularly for psychological health technologies.
It includes discrete questions to differentiate:
RCTs vs. observational studies
Clinical vs. real-world settings
Number of study arms (e.g., single, dual, multi-arm)
Whether AI model outputs are tested and validated, with questions focused on transparency in methods and accuracy
Criteria Categories
Evidence Type, Quantity & Study Design
Claimed Benefits & Alignment with Supporting Evidence
Source Credibility & Publication Format
Use of Behavior Change Models or Theoretical Frameworks
AI Model Testing & Output Accuracy
Domain 3: Regulation & Safety
The Regulation & Safety domain focuses on transparently capturing who is involved, what their qualifications are, and what role they play in the product’s development, delivery, or oversight.
This includes capturing:
If a qualified health professional is involved, and if so, their discipline, role, and level of involvement
Whether professionals are actively contributing (e.g., through testing, validation, content design, or live services) or listed in name only
If a robust safety management system exists — covering not just named oversight but also formal risk identification, mitigation, and reporting pathways
The domain also includes a set of criteria focused on clinical risk management documentation.
Criteria Categories
Health Professional Involvement & Role Transparency
Nature & Depth of Professional Contribution
U.S. FDA Regulatory Status & Device Classification
Safety in Peer Support & Communication Features
Risk Disclosure, Intended Use & Claim Accuracy
Clinical Safety Oversight & Governance Pathways
AI Governance & Model Assurance
Domain 4: Data & Privacy
The Data & Privacy domain evaluates whether products follow responsible and transparent data practices, with an emphasis on privacy rights, clarity, and protections — especially for users in psychological or vulnerable contexts.
It includes a refined approach to assessing HIPAA applicability, ensuring products fall under U.S. or equivalent legal obligations, and whether this is clearly communicated to users.
The domain also focuses on making privacy documentation more inclusive, addressing whether policies are:
Written in plain language
Accessible to a general reading level
Publicly available across key platforms
It also adds emphasis on:
Children’s data protection and parental consent
Secure user authentication and product-level access controls
Clear, visible pathways for raising privacy concerns or complaints
These criteria ensure that data practices are not only legally compliant but also understandable, fair, and protective — reinforcing user trust and psychological safety.
Criteria Categories
Refined HIPAA Applicability & Covered Entity Status
Transparency of Privacy Documentation
Clarity on Data Use, Collection & Sharing
User Rights
Children’s Data Protection & Consent Mechanisms
User-Level Authentication & Access Controls
Raising Concerns & Contact Pathways
Domain 5: Technical Security & Stability
The Technical Security & Stability domain evaluates how well a product protects user data, maintains uptime, and responds to faults — ensuring safe and reliable performance in real-world settings.
It covers:
Data handling and connectivity, including internet use, rollback capacity, and device-level storage
Operational stability, such as version control, issue resolution, monitoring, and long-term maintenance
Disaster recovery and continuity plans, including backup systems and decommissioning protocols
Testing and validation, including penetration, vulnerability, and load testing
Platform architecture, deployment type, and adherence to secure development practices (e.g., OWASP) Risk management and compliance, aligned with frameworks like ISO 27001, SOC 2, and NIST
This domain helps assess whether technical safeguards are not only in place but actively maintained and evidence-based, reducing risk to both users and clinical workflows.
Criteria Categories
Connectivity, Data Access & Device Storage
Version Control, Rollback & Maintenance Plans
Operational Monitoring & Issue Resolution
Disaster Recovery & Business Continuity
Security Testing & Vulnerability Detection
Architecture, Access Control & Deployment
Security Risk Management & Compliance Frameworks
Domain 6: Usability & Accessibility
The Usability & Accessibility domain assesses whether digital health products are inclusive, understandable, and practically usable across a wide range of user groups — with an emphasis on equity, flexibility, and responsiveness.
It includes criteria to evaluate:
Whether the product has been co-designed or tested with diverse populations, including people with lived experience, different cultural backgrounds, disabilities, and low digital literacy
The quality, clarity, and transparency of accessibility statements, including whether assistive technologies are supported and compliance with standards like WCAG and ADA best practice guidelines
Reading level and explanation of technical terms, to ensure clinical or digital content is accessible to those with cognitive impairments or limited literacy
Quality and responsiveness of user support — including the presence of clear contact methods and a commitment to resolving reported bugs, support requests, or clinical concerns.
Criteria Categories
Inclusive Design, Co-Design & Demographic Representation
Accessibility Statement & Design Standards Compliance
Support Tools & Comprehension Aids
Font, Visual & Presentation Customization Options
Notification Preferences & Privacy Controls
AI Accessibility & Feedback Integration
Support Access & Developer Responsiveness
AI Evaluation Framework
Clinical Context: Understanding the scope of influence
AI Function: What the AI component specifically does
AI Model Evaluation: Understanding the technology to identify inherent risks
Safety Design: Structural safeguards embedded in the system
Governance & Oversight: Operational controls and monitoring arrangements
Evidence: Testing and validation data along two distinct streams, model performance and control effectiveness
Expert Contributors
The APA Labs Digital Badge criteria were developed in collaboration with leading subject matter experts across psychology, digital health, clinical research, neuroscience, and mental health technology.
This multidisciplinary group brings together deep expertise from clinical practice, research, ethics, technology, and innovation to help ensure the criteria reflect the most important aspects of evaluating digital mental and behavioral health technologies.
For a full list of contributors, please see below.
Victoria Bangieva: Victoria Bangieva, PhD, is a licensed clinical psychologist who works at the intersection of clinical science and technology. She specializes in designing and disseminating digital measures and therapeutics to expand access to evidence-based tools and improve health outcomes. Her work is dedicated to driving the integration of digital health solutions into routine care and research.
Amber W. Childs: Dr. Amber W. Childs is a nationally recognized expert in child and adolescent mental health, and founder/CEO of The Dr. Amber Childs Advisory, a venture dedicated to improving mental health outcomes for youth. Currently an Associate Professor of Psychiatry at Yale School of Medicine, Dr. Childs is a serial founder (GROW, YMBCC, M-Select), award-winning innovator, and frequent media contributor (New York Times, Washington Post, CNBC, Hartford Courant). Dr. Childs earned her PhD from the University of Tennessee. She lives in Connecticut with her husband and two children.
Lindsay Childress Beatty: Dr. Lindsay Childress-Beatty is APA’s first Chief of Ethics, leading national and international conversations on psychological and organizational ethics. She has presented on ethics and AI at major venues, including the 2025 International Summit on Psychology and Global Health, CES 2024, and the APA Main Stage. A founding member of the Ethics Professionals Network, she previously served as APA’s Deputy General Counsel. Dr. Childress-Beatty is a licensed attorney with a PhD in Clinical Psychology from Columbia University, a JD from the University of Michigan, and an MPhil from the University of Cambridge.
David Cooper: David Cooper, PsyD. is a digital health expert who is currently the Executive Director of Therapists in Tech, the largest organization of clinicians in digital mental health. He has worked with organizations like the US Department of Defence, the AMA and FDA, Teladoc, and many top hospitals in the US on their digital health strategies and portfolios.
Karen Fortuna: Dr. Karen Fortuna is an Assistant Professor of Community and Family Medicine at Dartmouth and Founder of the Patient Innovation Lab, where she partners with patients to co-design technology solutions that support a long, healthy lifespan.
Leanna Fortunato: Leanna Fortunato is a licensed clinical psychologist with an interest in finding creative ways to harness technology to make high-quality mental health care more accessible and equitable for all. Fortunato supports OHCI’s efforts to operationalize strategies that promote practice innovation in the realms of digital mental health and measurement-based care. She has experience as a clinical administrator, practitioner, and consultant across a variety of settings including university-based mental healthcare, private practice, and digital mental health. Fortunato holds a PhD in Clinical Psychology from Eastern Michigan University and is licensed in Illinois and Virginia.
Trina Histon: Dr. Trina Histon is an internationally recognized expert in digital health, behavior change, and healthcare innovation. With over 20 years of experience at the intersection of clinical care, psychology, and technology, they bring academic rigor and real-world experience to partnerships focused on improving lives. Trina was previously VP of Clinical Product Strategy at Woebot Health and shaped national behavior change and digital health deployment efforts at Kaiser Permanente. They currently co-lead the UK’s Digital Adoption Workstream of the Mental Health Goals Program and serve several digital mental health companies.
Jessica Jackson: Dr. Jessica Jackson has over 15 years of experience turning conversations around mental health into actionable ecosystems of care. Serving on leadership advisory boards of the nation’s top mental health associations, behavioral health startups, and venture capital firms, Dr. Jackson helps innovators drive the future of mental health in ways that are profitable while remaining firmly equitable, inclusive, and accessible to every individual that needs it most.
Marie M. Onakmaiya: Marie M. Onakomaiya, PhD MPH is a neuroscientist, clinical epidemiologist, and founder of Metric Health, an AI-driven startup advancing brain injury assessment and monitoring. She is also a member of APA’s Mental Health Technology Advisory Committee. With a PhD from Dartmouth and an MPH from Columbia, Dr. Onakomaiya has built her career at the intersection of data, technology, and healthcare/public health innovation.
Stephen Schueller: Stephen Schueller, PhD is a Professor of Psychology and Informatics at the University of California, Irvine. He is a licensed clinical psychologist and a mental health services researcher. His work focuses on the development, evaluation, and implementation of technologies to improve mental health and mental health service delivery.
Jennifer Shannon: Dr. Jennifer Shannon is a practicing child psychiatrist at The Emily Program and a teaching faculty member at the University of Washington. She was previously a medical director at Cognoa, where she helped develop the first FDA-authorized diagnostic device for autism using machine learning. She is currently the co-founder and Chief Medical Officer of Glacis.
Hilary Weingarden: Dr. Weingarden is the Director of Clinical Research at HabitAware and a licensed psychologist providing evidence-based therapy for OCD, body dysmorphic disorder, and related conditions through a private practice in Massachusetts. She serves on the American Psychological Association's Mental Health Technology Advisory Committee, and before her current role, she was Assistant Director of the Massachusetts General Hospital Center for Digital Mental Health, a psychologist in the MGH Center for OCD and Related Disorders, and an Assistant Professor at Harvard Medical School. Her research, which leverages technology to improve assessments and treatments for mental health conditions and investigates the harmful role of shame in obsessive-compulsive and related disorders, has been funded by the National Institute of Mental Health and Harvard Medical School.
Rachel Wood: Dr. Rachel Wood holds a PhD in cyberpsychology with expertise at the intersection of AI and mental health. She is a speaker, workshop facilitator, and advisor. As the founder of the AI Mental Health Collective, she fosters clinician awareness of the impacts of AI and cultivates cross-disciplinary dialogue on responsible AI innovation. Dr. Wood’s work has been featured in TIME, ABC, the APA Monitor, International Business Times, Behavioral Health Business, and more.
C. Vaile Wright: Vaile Wright is a licensed psychologist and researcher focusing on developing strategies to leverage technology and data to address issues within health care including increasing access, measuring care, and optimizing treatment delivery at both the individual and system levels. Wright has maintained an active line of research with peer-reviewed articles in journals including Professional Psychology: Research and Practice, Law and Human Behavior, and the Journal of Traumatic Stress. As a spokesperson for APA, she has been interviewed by television, radio, print, and online media including CNN, NBC News, the Today Show, MSNBC, The Washington Post, and NPR on a range of topics including stress, politics, discrimination and harassment, COVID-19, serious mental illness, telehealth and technology, and access to mental health care. Wright received her PhD in counseling psychology from the University of Illinois, Urbana-Champaign in 2007, and is licensed in the District of Columbia.
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The APA Labs Digital Badge Solutions Library was developed in partnership with ORCHA.