Evidence map›Paper›PMID 41113761›Full record

ArticleJournal of medical extended reality2025

Expert Consensus Best Practices for the Safe, Ethical, and Effective Design and Implementation of Artificially Intelligent Conversational Agent (i.e., Chatbot/Virtual Human) Systems in Health Care Applications.

Albert Rizzo, Sharon Mozgai, Alexandros Sigaras, John E Rubin, Rohan Jotwani

Abstract read
In one paragraph

Article in Journal of medical extended reality, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Albert RizzoInstitute for Creative Technologies, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-2647-7731
Sharon MozgaiInstitute for Creative Technologies, University of Southern California, Los Angeles, California, USA.
Alexandros SigarasEnglander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, USA.ORCID https://orcid.org/0000-0002-7607-559X
John E RubinAnesthesiology, Weill Cornell Medical College, New York, New York, USA.
Rohan JotwaniAnesthesiology, Weill Cornell Medical College, New York, New York, USA.ORCID https://orcid.org/0000-0001-7605-1312

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of artificially intelligent conversational agents (AICAs), variously referred to as chatbots and virtual humans (VHs), is transforming health care delivery and education. This article explores our perspective on best practices for the evolution, potential, and ethical considerations of AICAs in clinical and educational contexts. Early applications of simulation technology in health care focused on productivity improvements, teletherapy, and virtual reality therapy applications. Recent technological advancements have enabled the development of high-fidelity extended reality systems and AICAs capable of engaging users in credible interactions. These systems leverage natural language processing, machine learning, large language models, and advanced VH authoring software to create interactive, personalized, and engaging experiences. Recent efforts in the creation of AICAs suggest significant potential benefits, including enhanced patient engagement, improved access to self-care resources, and low-stigma interaction environments. They have demonstrated promise in mental health support, providing a sense of safety and encouraging open disclosure. However, the rapid adoption of AICAs raises critical challenges, including safeguarding user privacy, ensuring system reliability, and addressing ethical concerns. Incidents of harm, such as inappropriate interactions and psychological distress, highlight the need for rigorous design and implementation best practices. This article outlines key principles for developing safe, effective, and equitable AICAs, emphasizing transparency in artificial intelligence (AI) identity, accountability, cultural sensitivity, and informed consent. Additionally, the authors advocate for robust privacy measures, adaptive learning capabilities, and evidence-based content validation to optimize user experience and maintain trust. To mitigate risks, a "human-in-the-loop" approach is recommended, ensuring health care professionals oversee AI-supported decisions. By adhering to these best practices, AICAs can enhance health care accessibility, support clinical training, and complement human professionals. This work aims to provide a foundation for the ethical and effective integration of AICAs, maximizing their potential while minimizing risks, ultimately advancing patient care and education in the digital age.

Indexed as

artificially intelligent conversational agents (AICAs)chatbotsextended reality (XR)health care technologylarge language models (LLMs)virtual humans

Identifiers

PMID41113761
PMCPMC12529073

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.