Patient-Therapist Conversations And Psychology Knowledge

An open-sourced dataset combines patient-therapist dialogues, psychology knowledge, and philosophy chats. It was created by alindumitru and last updated in June 2025. The data has undergone post-processing including toxicity filtering, duplicate removal, and anonymization.

Use Cases

• Fine-tune language models for therapeutic response generation using patient-therapist conversation examples.
• Train classifiers to identify psychological concepts or philosophical themes within the chat text.
• Develop anonymization or rephrasing models by studying the applied post-processing on the conversational data.
• Analyze discourse patterns in mental health support dialogues to inform chatbot design.

Strengths

• Data is processed for English language and filtered for toxicity.
• Includes duplicate removal and anonymization to enhance privacy and quality.

Limitations

• Exact size, row count, and specific column structure are unknown.
• Potential class or topic imbalance from merging multiple source datasets.
• Recency and representativeness of the source conversations are unspecified.

Provenance

Source

Aggregated from open-sourced datasets including 'CalebE new_mental_health_conversations' and the 'HOPE' dataset.

Collection Method

Mixture of source datasets with post-processing: toxicity filtering, duplicate removal, language detection (English), anonymization, rephrasing.

Time Range

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Freshness

Last updated on 2025-06-16.

Geography

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