Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology

作者: Ayah Zirikly , Dana Atzil-Slonim , Maria Liakata , Steven Bedrick , Bart Desmet

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摘要: Mental health is a pressing concern. Worldwide, mental health conditions are among the leading causes of disability [3, 7], and the global economic cost of mental health issues between 2011 and 2030, including neurological and substance use disorders, is projected to be more than $16 trillion [1]. In the US in 2020, suicide was in the top nine leading causes of death for people ages 10-64, and the second leading cause of death for people ages 10-14 and 25-34 [2]. Over the past several years, COVID-19 has created additional challenges to mental health. For instance, Sheridan et al.[5] found that suicide attempts in young children 10-12 have increased more than five-fold between 2010 and 2020. Furthermore, US Surgeon General Vivek Murthy in 2021 called for a nationwide response to the mental health crisis that youth especially are facing during the pandemic [4]. For the Eighth Workshop on Computational Linguistics and Clinical Psychology (CLPsych), we adopt the theme” mental health in the face of change”. This includes the kind of aspects natural language processing technologies need to address to deliver explainable and fair solutions that can be integrated in the clinical setting. Additionally, how these solutions can capture changes in mood over longitudinal and temporal data, which has been the focus of this year’s shared task. CLPsych was a hybrid workshop that accommodated both in-person and remote participation. It was collocated with NAACL’22, which took place in Seattle, Washington, USA on July 15th, 2022. Since 2014, CLPsych has been successful in bringing together people from different backgrounds (eg mental …

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