Prompt Engineering as a Safety Feature in Digital Health AI: Designing Conversational Systems for Sensitive Health Awareness

Abstract

Conversational artificial intelligence (AI) is increasingly used in digital health, telemedicine-related services, mental wellness, and behavioral health contexts. Although discussions of AI safety often center on factual accuracy, hallucination, privacy, crisis escalation, and human oversight, less attention has been paid to prompt engineering and response style as safety-relevant design features. This commentary argues that prompt engineering should be understood as a digital health AI safety mechanism because prompts do more than guide content generation; they shape the communicative conditions under which users interpret sensitive health concerns, regulate their responses, and decide whether to reflect, disengage, or seek support. Drawing on self-regulation theory and psychological reactance theory, the article explains how reflective AI responses may support self-monitoring, self-evaluation, and openness to help-seeking, whereas labeling, moralizing, or overly directive responses may increase shame, defensiveness, and disengagement. The commentary concludes by proposing design principles for safer conversational AI in sensitive health-awareness contexts.