Year: 2025
Type: preprint
Abstract: Suicide is a leading cause of death worldwide, and is one of the most devastating, complex, and perplexing of all human behaviors. Unfortunately, despite centuries of scientific and scholarly inquiry, suicidal thoughts and behaviors remain exceedingly difficult to understand, predict, and prevent. Fortunately, recent advances in mathematical, computational, and digital methods are providing new opportunities to capture and model the immense complexity of suicidal thoughts and behaviors. In this paper, we first provide a brief review of existing literature and then identify four priorities for future research, including: 1) rigorous conceptual and descriptive research, 2) formal theory development and refinement, 3) measurement in context and over time, and 4) prediction of group- and individual-level suicide risk. Finally, we discuss cross-cutting considerations related to ethical dilemmas, enhancing diversity, and training the next generation of scientists. Together, these future directions offer an actionable agenda to guide the future of suicide research and make meaningful progress towards reducing its global burden.
Institution: Yale University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4411945567