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5 - Using Algorithmic Solutions to Address Gatekeeper Training Issues for Suicide Prevention on College Campuses

from Part II - Optimizing Healthcare Systems

Published online by Cambridge University Press:  21 April 2022

By
Anthony Fulginiti ,
Aida Rahmattalabi ,
Jarrod Call ,
Phebe Vayanos  and
Eric Rice
Edited by
Sze-chuan Suen ,
David Scheinker  and
Eva Enns
Sze-chuan Suen
Affiliation:
University of Southern California
David Scheinker
Affiliation:
Stanford University, California
Eva Enns
Affiliation:
University of Minnesota
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Summary

In this chapter, we: (1) detail the problem scope and gatekeeper training as a solution to it, (2) delineate key issues that can impact GT as well as the consequences of ignoring them, (3) explore the value of social network information for GT recruitment, (4) explain the mathematical model of GT and an algorithmic solution approach that can account for gatekeeper, population, and institutional issues, and (5) describe experimental results that compare a novel algorithmic solution for GT recruitment with recruitment approaches that approximate common GT practice.

Keywords

gatekeeper trainingsuicidemental healthdepressionstudents
Type
Chapter
Information
Artificial Intelligence for Healthcare
Interdisciplinary Partnerships for Analytics-driven Improvements in a Post-COVID World
 , pp. 83 - 109
Publisher: Cambridge University Press
Print publication year: 2022

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