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    <identifier>10.57760/sciencedb.psych.00612</identifier>
    <datestamp>2025-09-17T08:42:10Z</datestamp>
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  <dc:date>2025-09-17</dc:date>
  <dc:title>Self-Help AI Psychological Counseling System Based on Large Language Models and Its Effectiveness Evaluation</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.psych.00612</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Project OverviewThis dataset supports the paper titled &amp;quot;Self-Help AI Psychological Counseling System Based on Large Language Models and Its Effectiveness Evaluation&amp;quot;. 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/ &amp;ndash; 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/ &amp;ndash; 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&amp;rsquo; 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.</dc:description>
  <dc:subject>large language models; chain-of-thought prompting; self-help psychological counseling; mental health interven-tion; artificial intelligence; human-computer interaction; AI personification; randomized controlled trial</dc:subject>
  <dc:creator>Huang</dc:creator>
  <dc:creator>Zhu Tingshao</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.3724/sp.j.1041.2025.2022</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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