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Full-Text Articles in Medicine and Health Sciences
Workshop On The Development And Evaluation Of Digital Therapeutics For Health Behavior Change: Science, Methods, And Projects, Alan J. Budney, Lisa A. Marsch, Will M. Aklin, Jacob T. Borodovsky, Mary F. Brunette, Andrew T. Campbell, Jesse Dallery, David Kotz, Ashley A. Knapp, Sarah E. Lord, Edward V. Nunes, Emily A. Scherer, Catherine Stanger, William C. Torrey
Workshop On The Development And Evaluation Of Digital Therapeutics For Health Behavior Change: Science, Methods, And Projects, Alan J. Budney, Lisa A. Marsch, Will M. Aklin, Jacob T. Borodovsky, Mary F. Brunette, Andrew T. Campbell, Jesse Dallery, David Kotz, Ashley A. Knapp, Sarah E. Lord, Edward V. Nunes, Emily A. Scherer, Catherine Stanger, William C. Torrey
Dartmouth Scholarship
The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that …
“Sorry I Didn’T Hear You.” The Ethics Of Voice Computing And Ai In High Risk Mental Health Populations, Fazal Khan, Christopher Villongco
“Sorry I Didn’T Hear You.” The Ethics Of Voice Computing And Ai In High Risk Mental Health Populations, Fazal Khan, Christopher Villongco
Scholarly Works
This article examines the ethical and policy implications of using voice computing and artificial intelligence to screen for mental health conditions in low income and minority populations. Mental health is unequally distributed among these groups, which is further exacerbated by increased barriers to psychiatric care. Advancements in voice computing and artificial intelligence promise increased screening and more sensitive diagnostic assessments. Machine learning algorithms have the capacity to identify vocal features that can screen those with depression. However, in order to screen for mental health pathology, computer algorithms must first be able to account for the fundamental differences in vocal characteristics …