Psychological Assessments with Large Language Models: A Privacy-Focused
  and Cost-Effective Approach
Sergi Blanco-Cuaresma
This study explores the use of Large Language Models (LLMs) to analyze text
comments from Reddit users, aiming to achieve two primary objectives: firstly,
to pinpoint critical excerpts that support a predefined psychological
assessment of suicidal risk; and secondly, to summarize the material to
substantiate the preassigned suicidal risk level. The work is circumscribed to
the use of "open-source" LLMs that can be run locally, thereby enhancing data
privacy. Furthermore, it prioritizes models with low computational
requirements, making it accessible to both individuals and institutions
operating on limited computing budgets. The implemented strategy only relies on
a carefully crafted prompt and a grammar to guide the LLM's text completion.
Despite its simplicity, the evaluation metrics show outstanding results, making
it a valuable privacy-focused and cost-effective approach. This work is part of
the Computational Linguistics and Clinical Psychology (CLPsych) 2024 shared
task.