Data · dataset · 2025
Stress Indicators Dataset for Mental Health Classification
Listed in Teesside University Research Data Repository
This dataset captures responses from 2,000 students regarding their experiences with stress, health, academics, and emotional well-being.
Description
The original dataset was collected via Google Forms survey and later expanded to ensure sufficient sample size for machine learning research. The survey items used a five-point Likert scale (1 = Not at all to 5 = Extremely).
All responses have been anonymized to protect participants’ privacy. The dataset is suitable for: Stress detection and classification (Eustress vs. Distress). Analyzing correlations between psychological, academic, and social stressors.
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Developing machine learning models for student mental health monitoring. 🔑 Key Features 👤 Demographics gender: 0 = Male, 1 = Female age: Numeric (18–22) 🧠 Emotional & Stress Indicators stress_experience heartbeat_palpitations anxiety_tension sleep_problems restlessness irritability sadness_low_mood loneliness_isolation concentration_problems 🩺 Physical & Health Indicators headaches health_issues weight_changes 📚 Academic & Environment Stressors academic_overload peer_competition low_academic_confidence subject_confidence academic_conflicts class_attendance professor_difficulties work_environment home_environment 💬 Social & Relationship Factors relationship_stress lack_relaxation_time 🎯 Target Variable stress_type (encoded): 0 = Distress (Negative Stress) 1 = Eustress (Positive Stress) 2 = Other / Mixed Stress 📂 Dataset File File: Stress_Dataset_Polished_Encoded.csv Rows: 2,000 Columns: 26 Missing Values: None Duplicates: None Target Variable: stress_type (3 classes)
Links
Where it is published
- DOI doi.org/10.17632/2gsjv8m7ch.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/2gsjv8m7ch.2 | 6 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |