Impact of online mental health screening tools on help-seeking, care receipt, and suicidal ideation and suicidal intent: Evidence from internet search behavior in a large U.S. cohort

Abstract

Introduction: Most people with psychiatric illnesses do not receive treatment for almost a decade after disorder onset. Online mental health screens reflect one mechanism designed to shorten this lag in help-seeking, yet there has been limited research on the effectiveness of screening tools in naturalistic settings.

Material and methods: We examined a cohort of persons directed to a mental health screening tool via the Bing search engine (n = 126,060). We evaluated the impact of tool content on later searches for mental health selfreferences, self-diagnosis, care seeking, psychoactive medications, suicidal ideation, and suicidal intent. Website characteristics were evaluated by pairs of independent raters to ascertain screen type and content. These included the presence/absence of a suggestive diagnosis, a message on interpretability, as well as referrals to digital treatments, in-person treatments, and crisis services.

Results: Using machine learning models, the results suggested that screen content predicted later searches with mental health self-references (AUC = 0⋅73), mental health self-diagnosis (AUC = 0⋅69), mental health care seeking (AUC = 0⋅61), psychoactive medications (AUC = 0⋅55), suicidal ideation (AUC = 0⋅58), and suicidal intent (AUC = 0⋅60). Cox-proportional hazards models suggested individuals utilizing tools with in-person care referral were significantly more likely to subsequently search for methods to actively end their life (HR = 1⋅727, p = 0⋅007).

Discussion: Online screens may influence help-seeking behavior, suicidal ideation, and suicidal intent. Websites with referrals to in-person treatments could put persons at greater risk of active suicidal intent. Further evaluation using large-scale randomized controlled trials is needed.

Publication
Journal of Psychiatric Research, 145
Damien Lekkas
Damien Lekkas
Data Scientist in Digital Mental Health

Research and development at the crossroads of mental health and technology. I use quantitative methods and AI to better understand psychopathology and behavior.