Jove
Visualize
Contact Us

Related Concept Videos

Patient-centered Care01:13

Patient-centered Care

Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
Therapeutic Communication01:30

Therapeutic Communication

Communication is a lifelong learning process. Through therapeutic communication, nurses can collect relevant assessment data, provide education and counseling, and interact during nursing interventions. Sending and receiving messages occur through verbal and nonverbal communication techniques and can happen separately or simultaneously.
Verbal communication depends on language or a prescribed way of using words so that people can share information effectively. The critical aspects of verbal...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Effectiveness of just-in-time adaptive interventions for improving mental health and psychological well-being: a systematic review and meta-analysis.

BMJ mental health·2025
Same author

How Do Recommended Elements in Suicide News Coverage Work? An Investigation of the Effect of Responsible Reporting and Readers' Reflectiveness on Suicide Prevention.

Health communication·2023
Same author

A Systematic Review of Responsibility Frames and Their Effects in the Health Context.

Journal of health communication·2022
Same author

The populist hotbed: How political attitudes, resentment, and justice beliefs predict both exposure to and avoidance of specific populist news features in the United States.

PloS one·2021
Same author

Investigating an Issue-Attention-Action Cycle: A Case Study on the Chronology of Media Attention, Public Attention, and Actual Vaccination Behavior during the 2019 Measles Outbreak in Austria.

Journal of health communication·2019
Same author

Is a Self-Monitoring App for Depression a Good Place for Additional Mental Health Information? Ecological Momentary Assessment of Mental Help Information Seeking among Smartphone Users.

Health communication·2019
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 16, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Patient-Centered Communication Preferences in AI-Powered Mental Health Chatbots: Evidence from Two Preregistered

Katharina Angermayr1,2, Nathalie Laura Neuendorf1,2, Sebastian Scherr1,2

  • 1Center for Interdisciplinary Health Research, University of Augsburg.

Health Communication
|June 15, 2026
PubMed
Summary

Users want AI mental health chatbots to feature reflective listening and multi-symptom assessment. Patient-centered communication features are highly valued in AI interactions for mental well-being.

More Related Videos

Humor or Rationality? The Neural Mechanisms of How Agent Type and Language Style Influence Satisfaction with Ride-Hailing Service Failure Recovery
09:53

Humor or Rationality? The Neural Mechanisms of How Agent Type and Language Style Influence Satisfaction with Ride-Hailing Service Failure Recovery

Published on: March 13, 2026

Related Experiment Videos

Last Updated: Jun 16, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Humor or Rationality? The Neural Mechanisms of How Agent Type and Language Style Influence Satisfaction with Ride-Hailing Service Failure Recovery
09:53

Humor or Rationality? The Neural Mechanisms of How Agent Type and Language Style Influence Satisfaction with Ride-Hailing Service Failure Recovery

Published on: March 13, 2026

Area of Science:

  • Human-Computer Interaction
  • Mental Health Technology
  • Health Communication

Background:

  • Mental health information access is transitioning from traditional search to conversational AI.
  • Patient-centered communication (PCC) principles are crucial for effective healthcare interactions.
  • Understanding user preferences for AI in mental health is essential for developing user-friendly tools.

Purpose of the Study:

  • To identify preferred communication features for AI chatbots in mental health.
  • To analyze user trade-offs between different feature bundles in AI mental health interactions.
  • To determine the value of patient-centered communication (PCC) aligned features in AI mental health chatbots.

Main Methods:

  • Two preregistered U.S. studies were conducted.
  • Study 1 utilized Best-Worst Scaling (BWS) with 414 participants to identify key PCC-aligned features.
  • Study 2 employed a Discrete Choice Experiment (DCE) with 268 participants to quantify feature trade-offs.

Main Results:

  • Users strongly preferred AI chatbots that simultaneously offered reflective listening and multi-symptom assessment.
  • Relational and clinical PCC-aligned features were highly valued in AI mental health interactions.
  • User preferences for communication features were consistent across different user groups.

Conclusions:

  • AI mental health chatbots should prioritize reflective listening and multi-symptom assessment features.
  • Incorporating relational and clinical PCC principles enhances user value in AI mental health tools.
  • User preferences guide the development of effective and accommodating AI mental health communication.