Exploring Public Awareness of Overwork Prevention With Big Data From Google Trends: Retrospective Analysis

Abstract

Background To improve working conditions and prevent illness and deaths related to overwork, the Taiwanese government in 2015, 2016, and 2018 amended regulations regarding working time, overtime, shifts, and rest days. Such policy changes may lead to a rising public awareness of overwork-related issues, which may in turn reinforce policy development. Objective This study aimed to investigate to what extent public awareness of overwork-related issues correlated with policy changes. Methods Policies, laws, and regulations promulgated or amended in Taiwan between January 2004 and November 2019 were identified. We defined 3 working conditions (overwork, long working hours, and high job stress) related to overwork prevention, generated a keyword for each condition, and extracted the search volumes for each keyword on the Google search engine as proxy indicators of public awareness. We then calculated the monthly percentage change in the search volumes using the Joinpoint Regression Program. Results Apparent peaks in search volumes were observed immediately after policy changes. Especially, policy changes in 2010 were followed by a remarkable peak in search volumes for both overwork and working hours, with the search volumes for overwork increased by 29% per month from June 2010 to March 2011. This increase was preceded by the implementation of new overwork recognition guidelines and media reports of several suspected overwork-related events. The search volumes for working hours also steadily increased, by 2% per month in September 2013 and afterward, reaching a peak in January 2017. The peak was likely due to the amendment to the Labor Standards Act, which called for “1 fixed and 1 flexible day off per week,” in 2016. The search volumes for job stress significantly increased (P=.026) but only by 0.4% per month since March 2013. Conclusions Over the past 15 years, Taiwanese authorities have revised and implemented several policies to prevent overwork-related health problems. Our study suggests a relationship between the implementation of policies that clearly defined the criteria for overwork and working hours and the rising public awareness of the importance of overwork prevention and shorter working hours.

Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index

“…Moreover, there is no time-lag for “fever”; this may attribute to the body temperature reporting mechanism adopted by both the Chinese government and local institutions. This reporting system required that people with fever be actively isolated and quarantined immediately to prevent the potential further spread of COVID-19 [ 33 , 34 ]. Therefore, people with fever would be isolated and confirmed subsequently.…”

Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu Index 

“…As there is no time-lag for "fever", this may attribute to the body temperature reporting mechanism adopted by both the Chinese government and local institutions. This reporting system required that people with fever should be actively isolated and quarantined immediately to obstruct the source of infection [33,34]. Therefore, people shown the symptom of fever would be isolated and con rmed subsequently.…”

Trends and Patterns in the Public Awareness of Palliative Care, Euthanasia, and End-of-Life Decisions in 3 Central European Countries Using Big Data Analysis From Google: Retrospective Analysis

“…Model selection was based on the Bayesian information criterion. This approach has already been established in previous studies investigating the impact of governmental policies on public awareness and internet search behavior [ 31 ].…”