Analisis Pengaruh Bekerja di Sektor Teknologi terhadap Akses Perawatan Kesehatan Mental menggunakan Causal Forest

Abstract

With the rapid growth of the technology sector and rising demands of digital work environments, mental health issues at work have become increasingly concerning. Employees in this field often face high workloads, demands for flexibility, and isolation from remote work—factors that significantly affect psychological well-being. This study investigates the causal impact of working in the technology sector on help-seeking behavior for mental health and explores effect heterogeneity based on individual characteristics. Data are drawn from the 2014 Mental Health in Tech Survey by Open Sourcing Mental Illness (OSMI), involving respondents from various countries, especially in North America and Europe. Estimation is performed using the Causal Forest method, a machine learning–based approach for estimating conditional causal effects while addressing complex variable interactions. The results show that adult male respondents in Europe who work remotely are the most likely to seek mental health services, possibly due to greater awareness and better access to psychological support. These findings emphasize the need for targeted mental health interventions tailored to individual characteristics, particularly in the high-pressure yet flexible technology sector.