# The Role of AI-Based Chatbots in Public Health Emergencies: A Narrative Review
## 1 Introduction
### The ELIZA Effect and Its Implications in Public Health Communication  
ELIZA was a prototypical chatbot developed in the 1960s by [PERSON] [16]. ELIZA mimicked a psychotherapist, engaging users in text-based conversations based on if-else statements and simple pattern matching [16]. Despite its simplicity, ELIZA demonstrated that machines could interact with humans while providing simple recommendations or elements of psychotherapeutic knowledge adapting to human requests [17]. In the psychological literature, it is known that the patient-psychoterapist dialogue is founded not only on knowledge but also on trust, engagement, care and empathy, which all promote a soothing environment [18]. [PERSON] observed an \"ELIZA effect\": Even when individuals were aware that ELIZA was a computer program, they still treated it as if it had genuine human qualities like intentions or emotions [16]. This phenomenon is linked with the theory of mind in developmental psychology [17; 19]. A theory of mind is the cognitive ability to understand that others have thoughts, feelings, and perspectives, potentially different from one's own. This ability typically develops in early childhood and is fundamental to human social interactions, enabling empathy, communication, and prediction of others' behavior [19]. Despite knowing ELIZA's mechanistic nature, users projected mental states onto the machine, assuming that ELIZA could understand and respond to their emotional cues. This projection, a manifestation of the ELIZA effect, illustrates that the theory of mind can extend to chatbots: Humans talking to even simple chatbots have the tendency to ascribe mental states to the latter and make sense of their behavior. The ELIZA effect and its theory-of-mind component have deep repercussions for public health communication. These psychological phenomena show that humans can engage psychologically with chatbots, ultimately building trustful rapports with them. In public health, trust is a critical emotion that underlies effective communication and the success of health interventions [20; 21]. Public health communication can be considered as a service where users are gaining health knowledge from one or several sources. Extensive psychological research [22] has shown that trust in service relationships can rise from affective phenomena (trusting a person perceived as friendly) or cognitive phenomena (trusting someone after a logical reasoning). Furthermore, several scientific studies have emphasized the importance of building trust between public health communicators and the public to ensure the effective dissemination of health information, e.g., open data [23], \begin{table}
\begin{tabular}{l l} \hline \hline
**Aspect** & **Key Points** \\ \hline Psychological Relevance & - & Theory of Mind: Users project mental states onto chatbots, enabling trust and engagement. \\  & - & Trust: Critical for effective public health communication and behavior change. \\  & - & Personification: Human-like traits (empathy, understanding) enhance user engagement and retention. \\ \hline Modern Chatbots (GPTs) & - & Advancements: GPTs enable human-like text generation and context understanding. \\  & - & Applications: Used in disease surveillance, health education, and behavior change. \\  & - & Challenges: Inherit human biases and exhibit non-human biases (e.g., hallucinations, overconfidence). \\ \hline Future Directions & - & Address biases (human and non-human) in chatbot responses. \\  & - & Foster interdisciplinary collaboration (psychology, computer science, public health) to optimize chatbot use in public health. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._and the adoption of recommended health behaviors, e.g., face masking [21]. The studies by [PERSON] and colleagues [24] highlight the concept of the social amplification of risk: the public's perception of risk is significantly influenced by the trust they have in the source of information.