Behavioral Medicine Counseling Dialogue Intent Classification Dataset
- Records
- 5000
- Size
- 0.5GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
This dataset contains excerpts from behavioral medicine counseling conversations between patients and professionals about health behavior change. Patient expressions are annotated with intents such as help seeking, information seeking, barrier disclosure, ambivalence, and goal setting. Each sample can include the conversation context, the patient's utterance, intent labels, and a rationale, supporting model fine-tuning, dialogue analysis, and evaluation without replacing professional clinical judgment.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| intent_labels | array | One or more intent categories expressed by the patient, such as help seeking, information seeking, barrier disclosure, ambivalence, or goal setting. |
| intent_rationale | string | A concise explanation of the textual evidence supporting the assigned intent label or labels. |
| conversation_text | string | The original dialogue excerpt between the patient and the professional, including relevant conversational context. |
| patient_utterance | string | The patient utterance or excerpt expressing the intent being annotated. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- Samples are drawn from counseling conversations between patients and professionals about health behavior change. They include dialogue excerpts, patient utterances, one or more intent labels, and a textual rationale for the annotation. Intent categories include help seeking, information seeking, barrier disclosure, ambivalence, and goal setting.
- How can the data support model training and evaluation?
- Conversation context and patient utterances can serve as inputs for intent classification, while intent labels provide supervised targets. Annotation rationales can assist with error analysis and label review. The data can support task-specific fine-tuning, benchmarking, and counseling dialogue analysis; check that the label definitions fit your target application.
- Is the dataset suitable for clinical decision-making?
- The data is intended to train and evaluate dialogue intent recognition, not to provide diagnoses or treatment recommendations, and should not be used alone for clinical decisions. Any deployment in a real service should be reviewed by qualified professionals and assessed for privacy, safety, and regulatory requirements.
- How can I obtain the data, and what are the licensing terms?
- Refer to the product page for the available delivery method, license scope, and terms, and contact the provider if any details are not stated. Before use, confirm that the license covers your intended activities, such as research, commercial model training, deployment, or redistribution.
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Cite this Work
@dataset{Mobiusi2026,
title={Behavioral Medicine Counseling Dialogue Intent Classification Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/bb1910613830ee244b4ffbd123853700?dataset_scene_id=4},
urldate={2026-10-13},
keywords={behavioral medicine dialogue data,counseling intent classification,patient intent recognition,health behavior change,dialogue text classification,behavioral medicine dataset,medical dialogue training data,intent recognition fine-tuning},
version={1.0}
}Using this in research? Please cite us.