Summary of Prior Studies on Student Mental Health Risk

A dataset summarizing prior studies on student mental health, authored by Dan Jiang and last updated on April 21, 2026. The dataset is stored in an XLS file with a size of 17.5 KB. It likely contains information synthesized from existing research on anxiety, depression, and stress among students.

Use Cases

• Benchmarking machine learning models for mental health prediction based on the described comparative analysis of SVM, Logistic Regression, Random Forest, LSTM, and FT-Transformer.
• Developing interpretable AI systems for student wellbeing based on the described integration of feature and temporal attention mechanisms.
• Analyzing patterns in student mental health risk factors based on the described feature engineering using entropy and uncertainty patterns.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• The associated research describes a model achieving 95% accuracy in empirical analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 17.5 KB, indicating limited scope.

Provenance

Source

figshare, authored by Dan Jiang.

Collection Method

Likely a literature review or synthesis of prior studies, as indicated by the title.

Time Range

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Freshness

Last updated 2026-04 21 17:32:52; freshness should be verified.

Geography

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