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Digital phenotyping in behavioral health research

Importance of digital behavioral health

Behavioral health is a term that encompasses a person’s habits, often manifesting as general wellbeing or mental health and substance use disorders. As the United States healthcare system continues to shift to focus on quality of care rather than quantity of care, the Centers for Medicare and Medicaid Services (CMS) have identified core measures of behavioral health that help establish value of care. Their 2022 core set of behavioral health measures lay out 20 areas that can be used to mark improvement in behavioral health, 7 for children and 13 for adults. These data can be collected through electronic health records, surveys, or administrative means, and serve as a solid base for the evaluation of quality care. However, the majority of behavioral health measures focus on when a patient is in the hospital or immediately following hospitalization, which represent the minority of cases in which behavioral health care is needed. There is a notable lack of access to behavioral health care and a shortage of mental health professionals, which illuminates the critical need for enabling measures of behavioral health using a digital health platform. This need was only heightened by the COVID-19 pandemic. As described by the Director of the National Institute on Mental Health, in June of 2020, 31% of respondents to a CDC survey experienced symptoms of anxiety or depression, 13% started or increased substance use, 26% showed stress-related symptoms, and 11% reported having serious thoughts of suicide in the past 30 days—these numbers were double those expected before the pandemic.

PROMPT Screen 3

Patient generated data and digital biomarkers of behavioral health

There are numerous validated methods to collect participant generated data on aspects of behavioral health. The Providing Mental Health Precision Treatment (PROMPT) Precision Health Study, for example, uses the MyDataHelps™ digital clinical trial and research platform to assess:

  • Depression through the Patient Health Questionnaire (PHQ)-9
  • Anxiety through the Generalized Anxiety Disorder (GAD)-7
  • Functional/perceived social support through the Interpersonal Support Evaluation List (ISEL)-12
  • Personality through the NEO-Five Factor Inventory
  • Suicide ideation through the Positive and Negative Suicide Ideation (PANSI)
  • Post-traumatic stress disorder through the PTSD Checklist (PCL)-5
  • Relation of family stress to mental/physical health outcomes in adulthood through the Risky Families Questionnaire
  • Sleep quality through the Pittsburgh Sleep Quality Index

Patient generated data is then combined with objective measures of behavioral health like sensor data within the app to create a complete digital phenotype. The PROMPT study then provides their participants with their daily mood, collected through ecological momentary assessments, and its correlation with controllable behaviors like steps, sleep, meditation, and electronic cognitive behavioral therapy. This promotes the patient’s understanding of their own patterns and allows them to adjust their habits as appropriate.

Potential to encourage behavior change

Studies have demonstrated that health apps, like the PROMPT study on the MyDataHelps™ platform, have a positive impact on behavioral health or clinical health outcomes and often garner high participant satisfaction. The potential to encourage behavior change is an important component of digital behavioral health, but there is a lack of standardization in the evaluation of that potential. The App Behavior Change Scale (ABACUS) is an emerging method for evaluating such potential uniformly across disciplines. The ABACUS consists of 21 questions focused on four categories: knowledge and information, goals and planning, feedback and monitoring, and actions. The rating system has been validated for internal consistency as well as inter-user reliability. It has great potential to impact digital behavioral health and when combined with other tools like MARS, a scale that measures app quality (e.g., aesthetics and function), it may provide a set of standards that guide the design of health apps moving forward. Learn how you can customize MyDataHelps™ to create a functional health app with high potential for behavior change.

Want to start building your next digital behavioral health project? Create a MyDataHelps™ account—free for up to 100 participants—or contact us to learn more!


  1. 2022 Core Set of Behavioral Health Measures for Medicaid and CHIP (Behavioral Health Core Set). (2022). Centers for Medicare & Medicaid Services.

  2. Goldman, M. L., Spaeth-Rublee, B., Nowels, A. D., Ramanuj, P. P., & Pincus, H. A. (2016). Quality Measures at the Interface of Behavioral Health and Primary Care. Current Psychiatry Reports, 18(4), 39.

  3. Gordon, J. (2021, April 9). One Year In: COVID-19 and Mental Health. National Institute of Mental Health (NIMH). Retrieved March 10, 2022, from

  4. Han, M., & Lee, E. (2018). Effectiveness of Mobile Health Application Use to Improve Health Behavior Changes: A Systematic Review of Randomized Controlled Trials. Healthcare Informatics Research, 24(3), 207.

  5. Hasselberg, M. J. (2019). The Digital Revolution in Behavioral Health. Journal of the American Psychiatric Nurses Association, 26(1), 102–111.

  6. McKay, F. H., Slykerman, S., & Dunn, M. (2019). The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change. JMIR mHealth and uHealth, 7(1), e11130.

  7. PROMPT Precision Health Study | University of Michigan Precision Health. (n.d.). Precision Health, University of Michigan. Retrieved March 1, 2022, from