  Virtual Mental Health Assistants (VMHAs) are seeing continual advancements to
support the overburdened global healthcare system that gets 60 million primary
care visits, and 6 million Emergency Room (ER) visits annually. These systems
are built by clinical psychologists, psychiatrists, and Artificial Intelligence
(AI) researchers for Cognitive Behavioral Therapy (CBT). At present, the role
of VMHAs is to provide emotional support through information, focusing less on
developing a reflective conversation with the patient. A more comprehensive,
safe and explainable approach is required to build responsible VMHAs to ask
follow-up questions or provide a well-informed response. This survey offers a
systematic critical review of the existing conversational agents in mental
health, followed by new insights into the improvements of VMHAs with contextual
knowledge, datasets, and their emerging role in clinical decision support. We
also provide new directions toward enriching the user experience of VMHAs with
explainability, safety, and wholesome trustworthiness. Finally, we provide
evaluation metrics and practical considerations for VMHAs beyond the current
literature to build trust between VMHAs and patients in active communications.
