Article

Perception of Safety in Behavioral Health Crisis Units among Patients and Care Partners versus Artificial Intelligence (AI): A Multimethod Study

2026-04-07

Abstract excerpt

<h4>Background</h4> Safety is a critical concern in behavioral health crisis units (BHCUs), where environmental risks (e.g., ligature points) can lead to injury to self or others. However, limited research has examined how perceived safety influences facility selection among patients and care partners, or how these perceptions align with AI-driven safety risk assessments in such environments. <h4>Method</h4> To...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 446e9d79-270c-5e43-b1f1-4bcc89c9bc26
DOI: 10.64898/2026.04.06.26350257

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Perception of Safety in Behavioral Health Crisis Units among Patients and Care Partners versus Artificial Intelligence (AI): A Multimethod StudyDOI 10.64898/2026.04.06.26350257Read

Controlling Safety of Artificial Intelligence-Based Systems in HealthcareSemantic proximity Read

From Advice to Action: Real-World Behaviour of Patients Using an Integrated Clinical AI for Navigating the Healthcare SystemSemantic proximity Read

The Cognitive Safety Net: Comparing Human and AI Diagnostic Reasoning during Complex Clinical SituationsSemantic proximity Read

Public Perceptions of Artificial Intelligence and Robotics in MedicineSemantic proximity Read

Is artificial intelligence for medical professionals serving the patients? Protocol for a mixed method systematic review on patient-relevant benefits and harms of algorithmic decision-making.Semantic proximity Read

Artificial intelligence meets LCA: a critical analysis from technical, ethical, and organizational perspectivesSemantic proximity Read

Human-Centered Design of an Artificial Intelligence (AI) Monitoring System: The Vanderbilt Algorithmovigilance Monitoring and Operations System (VAMOS)Semantic proximity Read

Taking the "Wild" out of Wildfires - Harnessing Data to Predict, Prevent, and Prepare for the FutureSemantic proximity Read

Evaluating the Human Safety Net: Observational study of Physician Responses to Unsafe AI Recommendations in high-fidelity SimulationSemantic proximity Read

Preparing for the Future: A Mixed Methods Study Protocol on AI Awareness and Educational Integration in Qatar’s Primary Health Care WorkforceSemantic proximity Read

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence researchSemantic proximity Read

Healthcare Workers’ Perspectives on Artificial Intelligence in Primary CareSemantic proximity Read