A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework

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This conceptual paper introduces MIND-SAFE, a framework for designing prompt engineering strategies in LLM-based mental health chatbots. It outlines a layered architecture that integrates evidence-based therapies like CBT and DBT with proactive risk detection and ethical safeguards. The resource is intended for developers and researchers seeking to align AI tools with clinical principles and responsible AI standards.

ID
3df613331c544b51
Source org
PubMed Central
Author
Sorio Boit (Grand Valley State University), Rajvardhan Patil (Grand Valley State University)
Published
2025-09-26
OA status
gold
DOI
10.2196/75078
PMID
Not recorded
PMCID
Not recorded
Citations
11

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BibTeX

@article{allodium:3df613331c544b51,
  title = {A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework},
  author = {Sorio Boit and Rajvardhan Patil},
  year = {2025},
  journal = {PubMed Central},
  doi = {10.2196/75078},
  url = {https://doi.org/10.2196/75078}
}

RIS

TY  - JOUR
TI  - A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework
AU  - Boit, Sorio
AU  - Patil, Rajvardhan
PY  - 2025
PB  - PubMed Central
DO  - 10.2196/75078
UR  - https://doi.org/10.2196/75078
ER  -

APA

Boit, S., & Patil, R. (2025). A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework. PubMed Central. https://doi.org/10.2196/75078

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