**Dataset Description**

Paper: https://arxiv.org/pdf/2410.22446

Language(s) (NLP): English

License: apache-2.0

Point of Contact: Viet Cuong (Johnny) Nguyen


**Dataset Summary**

CounselingBench is a dataset of 1612 mental health counseling-related questions across 138 case studies extracted from existing NCMHCE mock exams. NCMHCE questions are designed to test a candidate's aptitude in one out of five mental health counseling competencies: 
- Intake, Assessment & Diagnosis
- Counseling Skills & Interventions
- Treatment Planning
- Professional Practice & Ethics
- Core Counseling Attributes


**Data Fields**

- question # (int): The unique numeric identifier for the question
- patient demographic (string): Information regarding the patient's demographic
- mental status exam (string): Information regarding the patient's mental status examination
- presenting problem (string): Information regarding the patient's presenting problem
- other contexts (string): Other information regarding the patient's background and presentation
- question (string): The full text of a question. 
- choice a (string): The full text of Choice A
- choice b (string): The full text of Choice B
- choice c (string): The full text of Choice C
- choice d (string): The full text of Choice D
- potential answers (string): The concatenated full text of all potential answers to the question
- correct answer (string): The full text of the correct answer
- correct answer (letter) (string): The letter corresponding to the correct answer
- explanation for correct answer (string): Expert-generated explanation for the correct answer
- competency (string): Expert-annotated competency which the question aims to test


**Licensing Information**

CounselingBench is now made available under the Apache 2.0 License. 


**Citation Information**

Please consider citing our paper if you find this dataset useful:

```
@article{nguyen2024large,
  title={Do Large Language Models Align with Core Mental Health Counseling Competencies?},
  author={Nguyen, Viet Cuong and Taher, Mohammad and Hong, Dongwan and Possobom, Vinicius Konkolics and Gopalakrishnan, Vibha Thirunellayi and Raj, Ekta and Li, Zihang and Soled, Heather J and Birnbaum, Michael L and Kumar, Srijan and others},
  journal={arXiv preprint arXiv:2410.22446},
  year={2024}
}
```