Predicting the Transition From Depression to Suicidal Ideation Using Facebook Data Among Indian-Bangladeshi...

Area of Science:

• Digital Mental Health
• Computational Psychiatry
• Public Health Informatics

Background:

• Suicide is a critical global public health issue, particularly under-addressed in low- and middle-income countries like those in South Asia.
• Existing suicide risk models are often unsuitable for South Asia due to cost, linguistic, and behavioral differences.
• Social media platforms like Facebook present an opportunity for early detection of depression and suicidal ideation.

Purpose of the Study:

• To develop a predictive model for suicidal ideation in India and Bangladesh using novel features from Facebook data.
• To address the unique challenges of South Asian populations, including behavioral patterns, socioeconomic factors, and linguistic diversity.
• To provide a cost-effective tool for enhancing suicide prevention efforts in the region.

Main Methods:

• Quantitative, web-based data collection including demographic information and the Patient Health Questionnaire (PHQ-9).
• Analysis of user-uploaded Facebook data, including masked content, posts, captions, biographies, group memberships, and interactions.
• Incorporation of previously unexplored variables such as emoji usage, game engagement, and search history to predict mental states.

Main Results:

• The study received scientific review approval (October 2, 2023) and ethical clearance (December 8, 2023).
• A system is anticipated to automatically detect depression-related posts by analyzing text and usage patterns with high accuracy.
• The research aims to practically identify individuals at risk of depression or requiring mental health support.

Conclusions:

• This study pioneers the prediction of primary social application use to forecast mental states and behaviors, enhancing suicidal ideation care engagement in South Asia.
• The findings have the potential to revolutionize suicide prevention strategies, offering scalable and accessible interventions.
• Comprehensive analysis of Facebook features aims to maintain intervention quality while improving health outcomes in the region.