A Checklist for Trustworthy, Safe, and User-Friendly Mental Health Chatbots

2026-01-21

AI Summary

Current mental health chatbots lack systematic safety and ethical design standards, posing potential risks that remain inadequately validated. This study addresses this gap through a systematic literature review, synthesizing principles from human–computer interaction, ethical design, and mental health interventions to identify critical design shortcomings. It proposes, for the first time, a comprehensive checklist specifically tailored for mental health chatbots. This checklist functions dually as a development framework and an audit tool, offering developers and regulators structured, actionable guidance to advance responsible design practices. By doing so, it aims to enhance the sociotechnical reliability and user safety of digital mental health tools.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Natural Language Processing: Safety and Robustness
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Mental health concerns are rising globally, prompting increased reliance on technology to address the demand-supply gap in mental health services. In particular, mental health chatbots are emerging as a promising solution, but these remain largely untested, raising concerns about safety and potential harms. In this paper, we dive into the literature to identify critical gaps in the design and implementation of mental health chatbots. We contribute an operational checklist to help guide the development and design of more trustworthy, safe, and user-friendly chatbots. The checklist serves as both a developmental framework and an auditing tool to ensure ethical and effective chatbot design. We discuss how this checklist is a step towards supporting more responsible design practices and supporting new standards for sociotechnically sound digital mental health tools.

Problem

• mental health chatbots
• trustworthiness
• safety
• user-friendliness
• ethical design

Innovation

• mental health chatbots
• trustworthy AI
• safety checklist
• user-centered design
• ethical AI