Student Smoking, Alcohol, and Psychological Wellness Data

This dataset consists of 706 responses and 14 columns (features), focusing on the relationship between smoking, alcohol consumption, and psychological wellness among university students. It includes self-reported data on smoking and drinking habits, coping mechanisms, mental health, and help-seeking behaviors. The survey was designed to capture insights into how these behaviors impact students' overall well-being.

Data Collection: The data was collected through an online survey administered via Google Forms in [month/year]. Respondents provided information about their lifestyle habits, reasons for engaging in these behaviors, and their psychological wellness.

Key Features:
1. Demographics: Age, year of study, and field of study.
2. Smoking Habits: Frequency of smoking, age of starting, and reasons for smoking.
3. Alcohol Consumption: Frequency of alcohol use, typical weekly intake, and reasons for drinking.
4. Stress Management: Methods for coping with stress, including smoking and alcohol.
5. Mental Health: Self-reported psychological wellness and willingness to reduce or quit smoking and drinking.
6. Help-Seeking Behavior: Responses regarding help-seeking for mental health concerns.

This dataset can be used for:
1. Machine learning analysis to model and predict psychological wellness based on lifestyle behaviors.
2. Statistical studies on the interplay between smoking, alcohol, and mental health.
3. Development of intervention strategies to improve student well-being and reduce harmful habits.

Format: The dataset contains 14 columns with categorical, ordinal, and numerical data. It is formatted for ease of analysis and ready for use in statistical and machine learning applications.

本数据集由706份回应及14个列（特征）组成，聚焦于大学生吸烟、饮酒习惯与心理健康之间的关系。其中包含自我报告的吸烟和饮酒习惯、应对机制、心理健康状况及寻求帮助行为的数据。该调查旨在捕捉这些行为如何影响学生整体福祉的洞见。

数据收集：数据通过Google Forms在线问卷在[月份/年份]期间收集。受访者提供了有关其生活方式习惯、参与这些行为的原因以及其心理福祉的信息。

关键特征：
1. 人口统计学：年龄、学习年份及研究领域。
2. 吸烟习惯：吸烟频率、开始吸烟的年龄及吸烟原因。
3. 饮酒习惯：饮酒频率、典型每周摄入量及饮酒原因。
4. 压力管理：应对压力的方法，包括吸烟和饮酒。
5. 心理健康：自我报告的心理福祉及减少或戒烟戒酒的意愿。
6. 寻求帮助行为：关于心理健康问题寻求帮助的回应。

本数据集可用于：
1. 机器学习分析，基于生活方式行为对心理福祉进行建模和预测。
2. 对吸烟、饮酒与心理健康之间相互作用进行的统计研究。
3. 开发干预策略，以提升学生福祉并减少有害习惯。

格式：数据集包含14个列，包含分类、顺序和数值数据，格式便于分析，适用于统计和机器学习应用。