Like a Therapist, But Not: Reddit Narratives of AI in Mental Health Contexts

TL;DR

This study analyzes Reddit posts to understand how users perceive and relate to AI systems used for mental health support, revealing factors influencing engagement, trust, and relational dynamics in real-world contexts.

Contribution

It introduces a theory-informed annotation framework and applies a hybrid LLM-human pipeline to analyze large-scale discourse on AI in mental health.

Findings

Engagement is driven by outcomes, trust, and response quality.

Positive sentiment correlates with task and goal alignment.

Use for companionship often involves misaligned relationships and risks.

Abstract

Large language models (LLMs) are increasingly used for emotional support and mental health-related interactions outside clinical settings, yet little is known about how people evaluate and relate to these systems in everyday use. We analyze 5,126 Reddit posts from 47 mental health communities describing experiential or exploratory use of AI for emotional support or therapy. Grounded in the Technology Acceptance Model and therapeutic alliance theory, we develop a theory-informed annotation framework and apply a hybrid LLM-human pipeline to analyze evaluative language, adoption-related attitudes, and relational alignment at scale. Our results show that engagement is shaped primarily by narrated outcomes, trust, and response quality, rather than emotional bond alone. Positive sentiment is most strongly associated with task and goal alignment, while companionship-oriented use more often involves misaligned alliances and reported risks such as dependence and symptom escalation. Overall, this work demonstrates how theory-grounded constructs can be operationalized in large-scale discourse analysis and highlights the importance of studying how users interpret language technologies in sensitive, real-world contexts.