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Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries

BACKGROUND: Internet search query data reflect the attitudes of the users, using which we can measure the past orientation to commit suicide. Examinations of past orientation often highlight certain predispositions of attitude, many of which can be suicide risk factors. OBJECTIVE: To investigate the...

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Detalles Bibliográficos
Autores principales: Lee, Donghyun, Lee, Hojun, Choi, Munkee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768042/
https://www.ncbi.nlm.nih.gov/pubmed/26868917
http://dx.doi.org/10.2196/jmir.4981
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author Lee, Donghyun
Lee, Hojun
Choi, Munkee
author_facet Lee, Donghyun
Lee, Hojun
Choi, Munkee
author_sort Lee, Donghyun
collection PubMed
description BACKGROUND: Internet search query data reflect the attitudes of the users, using which we can measure the past orientation to commit suicide. Examinations of past orientation often highlight certain predispositions of attitude, many of which can be suicide risk factors. OBJECTIVE: To investigate the relationship between past orientation and suicide rate by examining Google search queries. METHODS: We measured the past orientation using Google search query data by comparing the search volumes of the past year and those of the future year, across the 50 US states and the District of Columbia during the period from 2004 to 2012. We constructed a panel dataset with independent variables as control variables; we then undertook an analysis using multiple ordinary least squares regression and methods that leverage the Akaike information criterion and the Bayesian information criterion. RESULTS: It was found that past orientation had a positive relationship with the suicide rate (P≤.001) and that it improves the goodness-of-fit of the model regarding the suicide rate. Unemployment rate (P≤.001 in Models 3 and 4), Gini coefficient (P≤.001), and population growth rate (P≤.001) had a positive relationship with the suicide rate, whereas the gross state product (P≤.001) showed a negative relationship with the suicide rate. CONCLUSIONS: We empirically identified the positive relationship between the suicide rate and past orientation, which was measured by big data-driven Google search query.
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spelling pubmed-47680422016-03-14 Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries Lee, Donghyun Lee, Hojun Choi, Munkee J Med Internet Res Original Paper BACKGROUND: Internet search query data reflect the attitudes of the users, using which we can measure the past orientation to commit suicide. Examinations of past orientation often highlight certain predispositions of attitude, many of which can be suicide risk factors. OBJECTIVE: To investigate the relationship between past orientation and suicide rate by examining Google search queries. METHODS: We measured the past orientation using Google search query data by comparing the search volumes of the past year and those of the future year, across the 50 US states and the District of Columbia during the period from 2004 to 2012. We constructed a panel dataset with independent variables as control variables; we then undertook an analysis using multiple ordinary least squares regression and methods that leverage the Akaike information criterion and the Bayesian information criterion. RESULTS: It was found that past orientation had a positive relationship with the suicide rate (P≤.001) and that it improves the goodness-of-fit of the model regarding the suicide rate. Unemployment rate (P≤.001 in Models 3 and 4), Gini coefficient (P≤.001), and population growth rate (P≤.001) had a positive relationship with the suicide rate, whereas the gross state product (P≤.001) showed a negative relationship with the suicide rate. CONCLUSIONS: We empirically identified the positive relationship between the suicide rate and past orientation, which was measured by big data-driven Google search query. JMIR Publications Inc. 2016-02-11 /pmc/articles/PMC4768042/ /pubmed/26868917 http://dx.doi.org/10.2196/jmir.4981 Text en ©Donghyun Lee, Hojun Lee, Munkee Choi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 11.02.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lee, Donghyun
Lee, Hojun
Choi, Munkee
Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title_full Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title_fullStr Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title_full_unstemmed Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title_short Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries
title_sort examining the relationship between past orientation and us suicide rates: an analysis using big data-driven google search queries
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768042/
https://www.ncbi.nlm.nih.gov/pubmed/26868917
http://dx.doi.org/10.2196/jmir.4981
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