The RHMCD-20 datasets for Depression and Mental Health Data Analysis with Machine Learning

Published: 8 January 2024| Version 2 | DOI: 10.17632/pxjmjyfdh2.2


the RHMCD-20 dataset, we took care to include information from a wide range of sources, including teenagers from Bangladesh, college students, housewives, professionals from businesses and corporations, and other people.This is survey data for Depression and Mental Health Data Analysis. Survey questions : Age: Represents the age of the participants. Gender: Indicates the gender of the participants. Occupation: Represents the participant's occupations. Days_Indoors :Indicates the number of days the participant has not been out of the house Growing_Stress: Indicates the participant's stress is increasing day by day (Yes/No). Quarantine_Frustration: Frustrations in the first two weeks of quarantine (Yes/Maybe/No). Changes_Habits: Represents major changes in eating habits and sleeping (Yes/Maybe/No). Mental_Health_History : A precedent of mental disorders in the previous generation (Yes/No). Weight_Change :Highlights changes in body weight during quarantine (Yes/Maybe/No) Mood_Swings: Represents extreme mood changes (Low/Medium/High). Coping_Struggles: The inability to cope with daily problems or stress (Yes/Maybe/No). Work_Interest :Represents whether the participant is losing interest in working (Yes/No). Social_Weakness :Conveys feeling mentally weak when interacting with others (Yes/No).



Daffodil International University, Dongseo University


Artificial Intelligence, Mental Health, Machine Learning, Big Data