Social Media and Suicide Prevention: Ethical Considerations
- Understand the potential utility of using social media data to predict suicidal risk.
- Critically evaluate the risk to benefit ratio by examining ethical issues involved with the application of machine learning methods to social media data.
No members of the planning committee, speakers, presenters, authors, content reviewers and/or anyone else in a position to control the content of this education activity have relevant financial relationships with any companies whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients.
In support of improving patient care, the University of Pittsburgh is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.
This activity is approved for the following credit: AMA PRA Category 1 Credit™. Other health care professionals will receive a certificate of attendance confirming the number of contact hours commensurate with the extent of participation in this activity.
The University of Pittsburgh designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Other Healthcare Professionals: Other health care professionals will receive a certificate of attendance confirming the number of contact hours commensurate with the extent of participation in this activity.
- 1.00 AMA PRA Category 1 Credit™The University of Pittsburgh School of Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
- 1.00 Attendance