Perceived Factors Analysis for Depression and Suicidal Ideation among Bangladeshi University Students Using Association Algorithm

Abstract

Depression stands as a prominent and prevalent mental health issue, representing a significant global public health concern. Its emergence can be attributed to diverse factors. Suicide stands as a prominent global cause of death, eliciting concern on a widespread scale. This study was to analyze the perceived factors for depression and suicidal ideation among Bangladeshi university students in Bangladesh. There are so many factors such as Loneliness, Hopelessness, Helplessness, Relationship Issues, Grade problems, Academic Pressure, Parental problems, Money problems, Social Comparison, Social Media Influence, Family Expectations, Lack of Sleep, Uncertain Future, Health Issues, Bullying, Substance Abuse and Unemployment etc. These factors vary among male and female students. Apriori association algorithm were used to calculate support, confidence and lift of factors sets. Frequent factors sets and relationship were found from the work using Apriori association algorithm. The work is an online survey-based study about psychological and stress status of participants and statistical analysis is used for concluding the results. The research participants are Bangladeshi university students, Data collection carried out by online questionnaire. The findings from data analysis indicated that academic pressure (72.41%), uncertain future (56.32%), hopelessness (48.28%), family expectation (47.13%), financial crisis (42.53%), loneliness (41.38%) and unemployment (37.93%) are the key factors. The prevention of suicides is achievable. Hence, identifying depression and forecasting the potential for suicide risk serves as a means to prevent instances of self-harm within the university student population.