Employee Mental Health and Burnout Records for Prediction Modeling

150,000 employee records intended for burnout prediction and mental health analysis. The dataset is hosted on Kaggle and includes platform tags indicating it may be synthetic. The author, organization, and last update date are unknown.

Use Cases

• Predicting employee burnout risk based on mental health indicators.
• Analyzing factors contributing to workplace mental health issues.
• Training classification models to identify at-risk employee profiles.
• Benchmarking synthetic data generation methods for HR analytics.

Strengths

• Contains 150,000 records, providing a substantial sample size for analysis.
• Platform tags suggest a focus on mental health and burnout, which are relevant for HR and healthcare analytics.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect synthetic bias inherent to its generation method on Kaggle.

Provenance

Source

Kaggle

Collection Method

Likely contains synthetic employee records for mental health analysis.

Time Range

null

Freshness

Last update date is unknown; freshness unverified.

Geography

null