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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)

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Provenance · 1 source records, 10 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/2gsjv8m7ch.26 h agoJSON v1
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