DNP Student Presents AI, Mental Health Research at SIGMA Conference
Claire Pettengill, MS’25, a student in the Psychiatric Mental Health Nurse Practitioner Program, presented “Algorithmic Justice in Mental Health: A Call for Ethical AI and Nursing Advocacy” this month at SIGMA’s Region 14 Research and Evidence-Based Practice Conference.
Her paper was selected by peer review for podium presentation at the conference, held March 1, 2026, at St. Peter’s University Hospital in New Brunswick, NJ. She also received a Regional Recognition certificate from SIGMA.
“The presentation examined the rapid growth of AI-driven mental health tools such as therapy chatbots, wellness apps, and algorithm-driven social media content,” Pettengill explained. “A central focus is the concept of algorithmic justice, which emphasizes protecting patient autonomy, privacy, and equity as digital mental health technologies expand.”
Risks associated with therapy apps, documentation tools, and social media include privacy concerns (many apps operate outside of HIPAA protections), algorithmic bias, and AI’s increasing skill at analyzing and even predicting emotional states, “while ethical and legal safeguards lag behind,” she notes in her paper.
“This gap increases risks related to privacy, bias, and inequity, particularly for marginalized communities,” she adds. “Psychiatric-mental health nurses (PMHNs) must be prepared to recognize these risks and advocate for patient safety, equity, and autonomy as AI becomes routine in care.”
Pettengill proposes a four-level nursing framework to ethically integrate AI in mental health: in clinical practice, with routine screening for AI use and patient education; practitioner oversight, through ethical evaluation of tools used in clinical workflow; community education to promote digital literacy and safer engagement with mental health apps; and policy advocacy in support of regulation and oversight of digital mental health technologies.
“Nurses should be actively involved in shaping how AI is implemented in health care,” Pettengill said. “Nurses collect much of the clinical data that digital systems rely on, yet many remain unaware of how these technologies are being developed and governed.”
She added: “Engaging nurses early is important to ensure AI tools support patient care and clinical workflows rather than creating additional documentation burdens similar to those experienced with early electronic medical record systems.”