Patient Depression Survey Responses with 14 Symptom Questions

Hamja S. Shaikh's Mental Health Detection Dataset contains survey responses from patients regarding symptoms associated with depression. Each patient answered 14 questions, with responses coded from 1 to 6 based on symptom frequency, and includes a column for overall depression state. The dataset is sourced from Kaggle and licensed under Apache 2.0.

Use Cases

• Train a depression state classifier based on the 14 coded symptom frequency responses.
• Analyze symptom correlation patterns based on the multi-question survey structure.
• Develop a feature importance model for depression indicators based on the coded survey columns.

Strengths

• Dataset includes a target column for overall depression state, facilitating supervised learning.
• Each record contains 14 coded symptom variables, providing multiple features per patient.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle, author Hamja S. Shaikh

Collection Method

Likely collected via patient surveys.

Time Range

null

Freshness

Last updated date is unknown.

Geography

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