Upload 3 files

LICENSE.txt

@@ -0,0 +1,14 @@
+Creative Commons Attribution 4.0 International (CC BY 4.0)
+
+You are free to:
+• Share — copy and redistribute the material in any medium or format.
+• Adapt — remix, transform, and build upon the material for any purpose, even commercially.
+
+Under the following terms:
+• Attribution — You must give appropriate credit, provide a link to the license,
+  and indicate if changes were made, without suggesting endorsement.
+
+Full license text: https://creativecommons.org/licenses/by/4.0/
+
+© 2025 Tarek Masryo
+This dataset is released under the CC BY 4.0 International license.

README.md

@@ -0,0 +1,81 @@
+# 🌐 Digital Habits and Mental Health  
+### Behavioral and Digital Wellbeing Dataset (2025)
+
+A curated dataset exploring how **digital lifestyles** shape **mental wellbeing** — linking screen time, phone use, sleep, and psychological factors such as stress, focus, and happiness.  
+Includes **3,500 anonymized participants** and **24 research-inspired features**, designed for **behavioral research**, **machine learning**, and **explainable AI**.
+
+---
+
+## 📘 Dataset Overview
+
+| Field | Description |
+|:--|:--|
+| **File name** | `Data.csv` |
+| **Rows** | 3,500 |
+| **Columns** | 24 |
+| **Target** | `high_risk_flag` |
+
+---
+
+## 🧠 Feature Groups
+
+**Demographics:** age · gender · region · income_level · education_level  
+**Digital Behavior:** daily_screen_time · phone_unlocks · notifications_per_day · social_media_hours · study_time · work_hours  
+**Mental Health Indicators:** stress_level · anxiety_level · depression_level · happiness_score · focus_score · productivity_score  
+**Derived Ratios:** screen_to_sleep_ratio · social_work_ratio · wellbeing_index  
+**Target:** `high_risk_flag` — binary wellbeing-risk indicator (0 = low, 1 = high)
+
+---
+
+## 🎯 Target Definition
+
+The target variable **`high_risk_flag`** labels individuals at elevated mental-health risk, defined by a composite of:
+- High digital engagement (screen time, unlocks, notifications)  
+- Elevated stress or anxiety  
+- Lower happiness/focus scores  
+
+Distribution: roughly **15–20 % high-risk**, aligning with behavioral research estimates.
+
+---
+
+## 🚀 Example Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("TarekMasryo/digital-habits-mental-health")
+
+df = dataset["train"].to_pandas()
+print(df.head())
+```
+
+---
+
+## 🔬 Research & Applications
+
+- Predict wellbeing risk from digital patterns  
+- Correlate stress, sleep, and screen exposure  
+- Build explainable models (SHAP / LIME)  
+- Segment behavioral profiles by lifestyle balance  
+- Apply calibration or threshold tuning for decision systems  
+
+---
+
+## 🧩 Reproducibility
+
+- No missing or duplicate values  
+- Deterministic preprocessing and schema  
+- Compatible with Kaggle, Colab, and Jupyter  
+
+---
+
+---
+
+## 🧭 Ethical Considerations
+Educational/research dataset only — **not** for clinical use, diagnosis, or treatment.
+
+## 📚 Citation
+Please cite the dataset URL on Hugging Face and the license below when using this data.
+
+## 📜 License
+**CC BY 4.0 (Attribution)** — Free to share and adapt with attribution.