Self-Help AI Psychological Counseling System Based on Large Language Models and Its Effectiveness Evaluation

Project OverviewThis dataset supports the paper titled "Self-Help AI Psychological Counseling System Based on Large Language Models and Its Effectiveness Evaluation". It includes all configuration files, source code, and experimental data used in the two-stage study. Study 1 focused on system construction and prompt optimization, while Study 2 evaluated the mental health effects of the AI counseling system through a randomized controlled trial (RCT).Directory Structure1. BOT_SYSTEM_SET/ – AI System ConfigurationLLMs_SET.json: Core API parameter settings for GPT-4o, including temperature, max_tokens, top_p, frequency_penalty, and presence_penalty.SYSTEM_CoT_PROMPT.json: Prompt engineering file containing the System Prompt and Chain-of-Thought strategy for guiding the LLM to act as a professional psychological counselor.2. DATA_AND_CODE/ – Experimental Data and Analysis ScriptsStudy 1: System construction and prompt optimizationE1_analysis_code.r: R script for analyzing model evaluation data.E1_results.txt: Comparison results of model performance before and after prompt engineering.E1_scb.csv: Evaluation data of baseline model using simple role prompts.E1_scp.csv: Evaluation data of baseline model using CoT-enhanced prompts.Study 2: Randomized Controlled Trial (RCT) for effectiveness evaluationE2_analysis_code.r: R script for linear mixed model (LMM) analysis.E2_results.txt: Output from the statistical modeling.E2_data.RData: Long-format RData file containing all participants’ measurements at T1, T2, and T3.NotesAll participant data have been anonymized and approved by the institutional ethics committee. Model configurations reflect the GPT-4o API settings as of June 2024. For reproducibility, please follow the script execution order precisely.ContactFor further information or collaboration inquiries, please contact the corresponding author.