Dataset Card for Vietnamese Mental Health Question Answering (VMHQA) Dataset

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Introduction

VMHQA is a pioneering Vietnamese Multiple-Choice Question Answering (MCQA) dataset designed specifically for the mental health domain. Comprising 10,000 high-quality question-answer pairs across 1,166 subjects, this dataset addresses critical gaps in mental health resources for Vietnamese-speaking communities.

Dataset Details

1. Domain-Specific Design
   Questions are crafted based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), ensuring relevance to mental health diagnoses.

2. High-Quality Annotations
   Each question includes multiple-choice options, the correct answer, and supporting paragraphs derived from trusted academic and medical sources, verified by mental health professionals.

3. Alignment with Medical Standards
   Adhering to the United States Medical Licensing Examination (USMLE) format, VMHQA ensures quality meets global medical standards.

4. Advanced Question Types
   Features diverse and complex question types, challenging AI models to reason, comprehend, and apply knowledge effectively.

5. Advancing Vietnamese NLP
   As the largest Vietnamese QA dataset in the mental health domain, VMHQA significantly contributes to the development of natural language processing (NLP) resources for a low-resource language.

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Dataset Overview

• Collected manually by human: 10,066
• Generated by GPT-4o: 2,200 records
• Generated by GPT-4o-mini: 5,000 records

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Dataset Structure

The dataset is provided in CSV format. Each row represents a single question-answer data point with the following columns:

• Topic: Main topic or category of the question.
• Question: The question text describing the scenario or problem.
• Answer: The correct answer option (1-based index corresponding to A, B, C, or D).
• A, B, C, D: The multiple-choice options for the question.
• Paragraph 1, Paragraph 2, Paragraph 3: Contextual paragraphs supporting the question and answers.
• Fact 1, Fact 2, Fact 3: Key supporting facts extracted from the paragraphs to justify the correct answer.
• Question_Type: The type of question (e.g., "Complex").
• Reference: Source link or reference for the information provided.
• ID: A unique identifier for each question-answer data point.
• Sub_topic: Specific subcategory of the topic.
• Subject: Broader subject area related to the topic.

This structured format ensures clarity and supports effective training and evaluation of AI models in the Vietnamese mental health domain.

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Dataset Creation

The VMHQA dataset was developed following these steps:

1. Source Compilation
   Data was gathered from trusted academic books, medical websites, and hospital records.

2. Annotation
   Psychology students crafted questions, answers, and supporting paragraphs following the USMLE format.

3. Expert Verification
   The dataset was validated by National Mental Hospital 2 to ensure accuracy and reliability.

4. Data Refinement

   • Removed duplicates and standardized formats.
   • Normalized topics and corrected inconsistencies.

5. Final Output
   Produced 10,000 high-quality records, ensuring robustness and relevance for mental health applications.

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Dataset Demo

Sample examples of the dataset are available in the Sample Data folder.

• Each sub-dataset (origin, GPT-4o, GPT-4o-mini) contains 10 examples.
• Use these examples to familiarize yourself with the dataset structure and format.

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Dataset Access

1. Sign the End User License Agreement (EULA) Form
   Download and sign the User Agreement form.
2. Submit the Form
   Send the signed form to the dataset owner via the email address provided in the form.
3. Receive Instructions
   Upon approval, you will be granted access to the full dataset on Hugging Face.

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Citation

When publishing research or presenting work that uses the VMHQA dataset, users must cite the dataset properly. The recommended citation in IEEE format is:

T. A. H. Nguyen, Q.-D. Nguyen, H. M. Nguyen, A. H. Nguyen, and L. Nguyen,
“VMHQA: A Vietnamese Multi-choice Dataset for Mental Health Domain Question Answering,”
EAI Endorsed Transactions on Scalable Information Systems,
vol. 12, no. 4, Sep. 2025, doi: 10.4108/eetsis.7678

Alternatively, you can cite it using the provided BibTeX entry:

@article{article,
  author  = {Nguyen, Loan and Nguyen, Tu and Nguyen, Quang-Dieu and Nguyen, Harius and Nguyen, Alfred},
  year    = {2025},
  month   = {09},
  pages   = {},
  title   = {VMHQA: A Vietnamese Multi-choice Dataset for Mental Health Domain Question Answering},
  volume  = {12},
  journal = {EAI Endorsed Transactions on Scalable Information Systems},
  doi     = {10.4108/eetsis.7678}
}

Failure to properly cite the dataset may result in revocation of access or denial of future dataset requests.

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Dataset Card Contact

For inquiries or support, please reach out to the dataset owner through the email provided in the EULA form.

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License

The dataset is distributed under specific terms outlined in the EULA form. Usage requires signing and adhering to the agreement's conditions.

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Thank you for your interest in the VMHQA Dataset! This resource aims to support advancements in Vietnamese NLP and the mental health domain.