# Can AI Help You Get Over Your Breakup? One Session with a Belief-Reframing Chatbot Shows Sustained Distress Reduction

arXiv: https://arxiv.org/abs/2605.03261 · HTML: https://mlsanity.com/paper/2605.03261/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 60 references that are in the map.
- First posted on arXiv 5 May 2026.

## Builds on (most cited first, 12 of 12)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
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- [Towards Understanding Sycophancy in Language Models](https://mlsanity.com/paper/2310.13548/) (2023)
- [Discovering Language Model Behaviors with Model-Written Evaluations](https://mlsanity.com/paper/2212.09251/) (2022)
- [FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://mlsanity.com/paper/2310.20410/) (2023)
- [Sycophancy in Large Language Models: Causes and Mitigations](https://mlsanity.com/paper/2411.15287/) (2024)
- [Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers](https://mlsanity.com/paper/2504.18412/) (2025)
- [The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Models](https://mlsanity.com/paper/2509.10970/) (2025)
- [Script-Based Dialog Policy Planning for LLM-Powered Conversational Agents: A Basic Architecture for an "AI Therapist"](https://mlsanity.com/paper/2412.15242/) (2024)
- [Supporting Effective Goal Setting with LLM-Based Chatbots](https://mlsanity.com/paper/2602.08636/) (2026)
- [AI-Assisted Goal Setting Improves Goal Progress Through Social Accountability](https://mlsanity.com/paper/2603.17887/) (2026)

## Abstract (arXiv)

Romantic breakups are among the most common and intense sources of psychological distress. We evaluated *overit*, a single-session AI chatbot that uses cognitive reappraisal to address breakup distress, informed by memory reconsolidation theory. In a pre-registered randomized controlled trial, 254 adults in the United States and United Kingdom who had experienced a romantic breakup were assigned to either an initial survey assessment followed by an AI chat session or to a survey-only control. Breakup distress was measured at baseline, 7 days, and again at an exploratory 1-month follow-up using the Breakup Distress Scale. Participants assigned to *overit* showed a significantly greater reduction in breakup distress than controls at 7 days (time-by-condition interaction B = -5.36, SE = 1.19, p < .001; completer-based d = -0.70). A smaller but still significant treatment advantage remained detectable at the exploratory 1-month follow-up among post-session completers (B = -2.92, SE = 1.22, p = .017). Exploratory post hoc moderation suggested a larger effect among male participants (B = 7.78, p = .003). These results suggest that a brief AI chatbot conversation can meaningfully reduce breakup distress, with exploratory evidence that a smaller advantage persists over the following month. Future work should test the intervention against active controls, evaluate repeated-session use, and recruit more diverse samples.
