# MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling

arXiv: https://arxiv.org/abs/2310.05231 · HTML: https://mlsanity.com/paper/2310.05231/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 116 references that are in the map.
- First posted on arXiv 8 Oct 2023.

## Builds on (most cited first, 18 of 18)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://mlsanity.com/paper/2107.13586/) (2021)
- [Survey of Hallucination in Natural Language Generation](https://mlsanity.com/paper/2202.03629/) (2022)
- [Recipes for building an open-domain chatbot](https://mlsanity.com/paper/2004.13637/) (2020)
- [Deep Learning for Medical Image Analysis](https://mlsanity.com/paper/1708.08987/) (2017)
- [A Survey of Hallucination in Large Foundation Models](https://mlsanity.com/paper/2309.05922/) (2023)
- [AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts](https://mlsanity.com/paper/2110.01691/) (2021)
- [Neural Approaches to Conversational AI](https://mlsanity.com/paper/1809.08267/) (2018)
- [Challenges in Building Intelligent Open-domain Dialog Systems](https://mlsanity.com/paper/1905.05709/) (2019)
- [Sparks: Inspiration for Science Writing using Language Models](https://mlsanity.com/paper/2110.07640/) (2021)
- [Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Support](https://mlsanity.com/paper/2307.15810/) (2023)
- [Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support](https://mlsanity.com/paper/2203.15144/) (2022)
- [Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data](https://mlsanity.com/paper/2301.05843/) (2023)
- [ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events](https://mlsanity.com/paper/2309.12244/) (2023)
- [Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Models](https://mlsanity.com/paper/2205.00176/) (2022)
- [An Evaluation of Generative Pre-Training Model-based Therapy Chatbot for Caregivers](https://mlsanity.com/paper/2107.13115/) (2021)
- [CatAlyst: Domain-Extensible Intervention for Preventing Task Procrastination Using Large Generative Models](https://mlsanity.com/paper/2302.05678/) (2023)

## Built on by (most cited first, 30 of 50)

- [Large Language Models in Mental Health Care: a Scoping Review](https://mlsanity.com/paper/2401.02984/) (2024)
- [MindScape Study: Integrating LLM and Behavioral Sensing for Personalized AI-Driven Journaling Experiences](https://mlsanity.com/paper/2409.09570/) (2024)
- [Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review](https://mlsanity.com/paper/2501.12557/) (2025)
- [Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation](https://mlsanity.com/paper/2502.02780/) (2025)
- [Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App](https://mlsanity.com/paper/2404.00487/) (2024)
- [AI Chatbots for Mental Health: Values and Harms from Lived Experiences of Depression](https://mlsanity.com/paper/2504.18932/) (2025)
- [Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers](https://mlsanity.com/paper/2506.15047/) (2025)
- [Exploring User Security and Privacy Attitudes and Concerns Toward the Use of General-Purpose LLM Chatbots for Mental Health](https://mlsanity.com/paper/2507.10695/) (2025)
- [A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions](https://mlsanity.com/paper/2502.11095/) (2025)
- [Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives](https://mlsanity.com/paper/2507.15783/) (2025)
- [Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale](https://mlsanity.com/paper/2505.23785/) (2025)
- [CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients](https://mlsanity.com/paper/2402.04620/) (2024)
- [Private Yet Social: How LLM Chatbots Support and Challenge Eating Disorder Recovery](https://mlsanity.com/paper/2412.11656/) (2024)
- [AACessTalk: Fostering Communication between Minimally Verbal Autistic Children and Parents with Contextual Guidance and Card Recommendation](https://mlsanity.com/paper/2409.09641/) (2024)
- [Applying and Evaluating Large Language Models in Mental Health Care: A Scoping Review of Human-Assessed Generative Tasks](https://mlsanity.com/paper/2408.11288/) (2024)
- [Understanding Communication Preferences of Information Workers in Engagement with Text-Based Conversational Agents](https://mlsanity.com/paper/2410.20468/) (2024)
- [ExploreSelf: Fostering User-driven Exploration and Reflection on Personal Challenges with Adaptive Guidance by Large Language Models](https://mlsanity.com/paper/2409.09662/) (2024)
- [AI-induced sexual harassment: Investigating Contextual Characteristics and User Reactions of Sexual Harassment by a Companion Chatbot](https://mlsanity.com/paper/2504.04299/) (2025)
- [Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness](https://mlsanity.com/paper/2407.13067/) (2024)
- [AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking](https://mlsanity.com/paper/2503.03532/) (2025)
- [StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework](https://mlsanity.com/paper/2506.14159/) (2025)
- [The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systems](https://mlsanity.com/paper/2411.01228/) (2024)
- [Position: Beyond Assistance -- Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care](https://mlsanity.com/paper/2503.16456/) (2025)
- [RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools](https://mlsanity.com/paper/2503.21888/) (2025)
- [Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making](https://mlsanity.com/paper/2502.18853/) (2025)
- [State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Living](https://mlsanity.com/paper/2510.14513/) (2025)
- [Vidmento: Creating Video Stories Through Context-Aware Expansion With Generative Video](https://mlsanity.com/paper/2601.22013/) (2026)
- [Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions](https://mlsanity.com/paper/2409.02244/) (2024)
- [Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling](https://mlsanity.com/paper/2503.24145/) (2025)
- [A Checklist for Trustworthy, Safe, and User-Friendly Mental Health Chatbots](https://mlsanity.com/paper/2601.15412/) (2026)

## Abstract (arXiv)

In the mental health domain, Large Language Models (LLMs) offer promising new opportunities, though their inherent complexity and low controllability have raised questions about their suitability in clinical settings. We present MindfulDiary, a mobile journaling app incorporating an LLM to help psychiatric patients document daily experiences through conversation. Designed in collaboration with mental health professionals (MHPs), MindfulDiary takes a state-based approach to safely comply with the experts' guidelines while carrying on free-form conversations. Through a four-week field study involving 28 patients with major depressive disorder and five psychiatrists, we found that MindfulDiary supported patients in consistently enriching their daily records and helped psychiatrists better empathize with their patients through an understanding of their thoughts and daily contexts. Drawing on these findings, we discuss the implications of leveraging LLMs in the mental health domain, bridging the technical feasibility and their integration into clinical settings.