# How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study

arXiv: https://arxiv.org/abs/2503.17473 · HTML: https://mlsanity.com/paper/2503.17473/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2025.

## Built on by (most cited first, 22 of 22)

- [Seven simple steps for log analysis in AI systems](https://mlsanity.com/paper/2604.09563/) (2026)
- [ComBodied Agents: a New Paradigm of Human-Centric Agentic AI](https://mlsanity.com/paper/2608.10915/) (2026)
- [Invisible failures in human-AI interactions](https://mlsanity.com/paper/2603.15423/) (2026)
- [Disclosure By Design: Identity Transparency as a Behavioural Property of Conversational AI Models](https://mlsanity.com/paper/2603.16874/) (2026)
- [Understanding Risk and Dependency in AI Chatbot Use from User Discourse](https://mlsanity.com/paper/2602.09339/) (2026)
- [Unilateral Relationship Revision Power in Human-AI Companion Interaction](https://mlsanity.com/paper/2603.23315/) (2026)
- [Brief chatbot interactions produce lasting changes in human moral values](https://mlsanity.com/paper/2604.21430/) (2026)
- [RealityTest: How People Probe AI Identity and Whether Models Disclose It](https://mlsanity.com/paper/2606.00168/) (2026)
- [Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration](https://mlsanity.com/paper/2606.18259/) (2026)
- [Optimising for Flourishing: Flourishing Metrics and Return on Flourishing as Success Criteria for Artificial Intelligence and Post-AGI Economic Systems](https://mlsanity.com/paper/2608.00151/) (2026)
- [Structure-agnostic Causal Representation Learning](https://mlsanity.com/paper/2610.00968/) (2026)
- [How Value Induction Reshapes LLM Behaviour](https://mlsanity.com/paper/2605.07925/) (2026)
- [VET: A Framework for Analyzing AI Discourse](https://mlsanity.com/paper/2606.01929/) (2026)
- [Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connection](https://mlsanity.com/paper/2606.04150/) (2026)
- [Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts](https://mlsanity.com/paper/2606.18258/) (2026)
- [AI Companions as Hyper Attachment and Caregiving Targets](https://mlsanity.com/paper/2606.20589/) (2026)
- [Alignment Plausibility: A New Standard for Assuring AI in Healthcare](https://mlsanity.com/paper/2607.07766/) (2026)
- [Understanding Cognition-Induced Risks in Agentic AI Systems](https://mlsanity.com/paper/2608.15304/) (2026)
- [How a Chatbot's Response Style Shapes a Classroom: A Multi-Agent Simulation of Students Consulting AI](https://mlsanity.com/paper/2609.05018/) (2026)
- [LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions](https://mlsanity.com/paper/2609.14849/) (2026)
- [Safety Nudges: User-Facing Interventions for Real-Time AI Risk Awareness](https://mlsanity.com/paper/2609.26865/) (2026)
- [RELATE: An Evaluation Framework for measuring Relational Orientation of Large Language Models](https://mlsanity.com/paper/2610.09569/) (2026)

## Abstract (arXiv)

As people increasingly seek emotional support and companionship from AI chatbots, understanding how such interactions impact mental well-being becomes critical. We conducted a four-week randomized controlled experiment (n=981, >300k messages) to investigate how interaction modes (text, neutral voice, and engaging voice) and conversation types (open-ended, non-personal, and personal) influence four psychosocial outcomes: loneliness, social interaction with real people, emotional dependence on AI, and problematic AI usage. No significant effects were detected from experimental conditions, despite conversation analyses revealing differences in AI and human behavioral patterns across the conditions. Instead, participants who voluntarily used the chatbot more, regardless of assigned condition, showed consistently worse outcomes. Individuals' characteristics, such as higher trust and social attraction towards the AI chatbot, are associated with higher emotional dependence and problematic use. These findings raise deeper questions about how artificial companions may reshape the ways people seek, sustain, and substitute human connections.
