Mind Bloom: a Mobile Application for Mental Health Self-Care
Issued Date
2025-01-01
Resource Type
Scopus ID
2-s2.0-105032390659
Journal Title
Jcsse 2025 22nd International Joint Conference on Computer Science and Software Engineering
Start Page
277
End Page
283
Rights Holder(s)
SCOPUS
Bibliographic Citation
Jcsse 2025 22nd International Joint Conference on Computer Science and Software Engineering (2025) , 277-283
Suggested Citation
Tangsripairoj S., Kodcharin S., Autthasom H., Kumeak K. Mind Bloom: a Mobile Application for Mental Health Self-Care. Jcsse 2025 22nd International Joint Conference on Computer Science and Software Engineering (2025) , 277-283. 283. doi:10.1109/JCSSE67377.2025.11297956 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115749
Title
Mind Bloom: a Mobile Application for Mental Health Self-Care
Author(s)
Author's Affiliation
Corresponding Author(s)
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Abstract
In recent years, mental health has become an increasingly prominent concern in society due to rapidly changing lifestyles, heightened stress, anxiety, and mounting pressures. Mental health care is therefore essential, as it directly impacts personal well-being and quality of life. Tools that support systematic assessment, monitoring, and promotion of mental health self-care can empower individuals to take proactive and consistent care of their mental well-being. Mind Bloom is a mobile application designed to support holistic mental health care. It comprises eight core functions: mental health assessment, mood tracking, wellness activities, emotional expression, mental health education, notification reminder, supporting services, and motivation building. This application enables users to systematically assess, monitor, and manage their mental health by recording their daily emotions, engaging in personalized activities, and accessing relevant information and resources. The goal of the application is to improve users' quality of life, promote sustainable mental well-being, and contribute to building a mentally healthier society. The evaluation results with 40 users showed high satisfaction levels, with 92.5% of participants rating their experience as 'Satisfied' or 'Very Satisfied,' and no users expressing dissatisfaction. The most beneficial features identified were mental health assessment, mood tracking, and self-care learning resources.
