Quantifying and Understanding Gender and Cross Cultural Differences in Mental Health Expression via Social Media
For a long time, mental illness was treated as a gender and culture neutral problem. However recent research shows that several social and psychological characteristics are unique to women [6] and hence there is a need to investigate in depth the causes and antecedents of emotional distress in women [49] In developing countries, socio political and economic issues such as poverty, inequalities in the workplace, societal and cultural expectations of women are often known to heighten women's risk to distress and mental illness [54] However, the gender and cultural dimensions of mental health, especially in countries of the majority world, are less understood1. The United Nations' Millennium Development Goals2, established in 2000, notes that the majority of data we have on global burden of mental illnesses comes from massive data aggregation exercises conducted only once every few years [38] This data often does not include gender information; and often different countries have different policies and practices in place in terms of how mental illnesses are assessed [48] Overlooking gender or culture based differences can have drastic consequences. This includes, misdiagnosis, misappropriation of interventions, constrained help seeking along stereotypical lines, and a "one size fits all" approach to extend help to those who may have unique needs [49, 48] With the lack of an adequate global surveillance system, and with the accelerating pace of economic and cultural change, more frequently updated information on mental disorders for different gender and cultural subgroups is needed [39, 41] especially from subgroups who may not necessarily appear in formal statistical surveys of health and well being. In recent years, a new research direction has established social media data as a way to understand mental health challenges in people [16, 14, 26] It has been found that these approaches can greatly supplement and complement traditional mental health assessments, such as the Behavioral Risk Factor Surveillance System (BFRSS) survey conducted by the Centers for Disease Control and Prevention (CDC) in the US [13, 12, 10, 18] However, cultural and gendered expression of different subgroups may differ markedly from the "typical" largely western populations, on which these current social media investigations of mental health are based [16, 14] Per the perspective laid out by postcolonial computing, rarely are analytical insights and intervention mechanisms able to be transplanted without modification from one subgroup to another, and still provide the same value [29] Therefore, identifying gender based and cross cultural context is critical in the use of such passively sensed big data for making sense of mental health and well being.