Skip to main content
Skip to main content

Philip on mental health

September 24, 2026 Linguistics

Philip Resnick image

Using computer assisted text analysis to help clinicians.

On September 22, CBS News ran a story on suicide prevention, reporting research led by Philip. In "The 16,648 reasons to live instead of dying by suicide: Insights from a computer-assisted content analysis," Philip and his collaborators analyze a corpus of texts, by people who had considered suicide, on the topic of what helped them stay alive. They identify common themes, such as not wanting to hurt loved ones, or looking forward to small future pleasures, which may in turn be useful to clinicians seeking to help suicidal patients. Says Philip, "I think one of the most interesting things that came out of this was small things can actually have a big effect." The paper, published in Scientific Reports, is abstracted below.


Most research on suicide focuses on the progression toward lethal action. Fewer studies have looked at individuals’ past experiences with the desire to die and why they did not die by suicide. Moreover, the existing use of reasons to live in assessment and treatment is generally grounded in inventories of questions that, while groundbreaking and well validated, were developed decades ago and without a focus on individuals’ lived experiences. In this study, an online user’s query to formerly suicidal people on the popular Reddit platform afforded a novel opportunity to investigate reasons people lived in a large, naturally occurring sample of 16,648 self-reports about their experiences. Using a new method for computer-assisted qualitative content analysis, we identify categories, and themes organizing those categories, that affirm prior work and also provide new perspectives on that work, as well as suggesting connections between ideas in the literatures on reasons people die, reasons people live, and subjective and psychological well-being. The study highlights the value of computer-assisted methods as a way of achieving both scale and interpretable results, and it identifies a number of theoretical and clinical avenues for further investigation.