pandalla/datatager_social_and_emotional_risk_assessment

---
license: apache-2.0
---

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# Social and Emotional Risk Assessment

## Prompt for Training
When training your model with this dataset, prepend the following prompt to each input instance:

```
根据提供的心理咨询问题，自动生成包含风险评估和建议的回答。识别咨询中的关键信息，评估咨询者可能的心理状态，然后提供针对性的支持和建议。
```

## Description
AnyTaskTune is a publication by the DataTager team. We specialize in rapidly training large models suitable for specific business scenarios through task-specific fine-tuning. We have open-sourced several datasets across various domains such as legal, medical, education, and HR, and this dataset is one of them.

This dataset, titled "Social and Emotional Risk Assessment," is part of an initiative by the DataTager team under the AnyTaskTune publication. It focuses on analyzing and assessing the emotional and social risks presented in interpersonal interactions. This dataset aims to help in identifying the severity of emotional distress or social disconnection that individuals may express during consultations or interactions, thereby aiding professionals to provide timely and appropriate support.

## Usage

This dataset is particularly valuable for training AI systems aimed at mental health assessments and therapeutic dialogue processing. By recognizing and categorizing the risk levels associated with different emotional and social inquiries, these AI models can assist mental health professionals in prioritizing cases and formulating intervention strategies. This not only helps in managing the caseload effectively but also improves the quality of mental health care provided. Additionally, the dataset can be utilized in training settings to educate emerging psychologists and counselors on how to effectively assess and respond to various emotional and social challenges.

## Citation

Please cite this dataset in your work as follows:
```
@misc{ Extract Medical Information Dataset,
author = {DataTager},
title = {Extract Medical Information Dataset},
year = {2024},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\\url{https://github.com/PandaVT/DataTager}}
}
```