US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic

Riddell, Chris; Farkas, Kriszta; Neumann, Krista; Santaularia, N. Jeanie; Ahern, Jennifer; Mason, Susan M.

doi:10.1016/j.ypmed.2022.107215

Cited by 2 publications

(2 citation statements)

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“…In the past decades, the internet and social media have been extensively used as a source of information and to predict the public interest using search trends. In this regard, Google Search Trends emerged as a widely accepted and extensively used tool (Lin et al , 2020; Riddell et al , 2022). The analysis of relative search volumes (RSVs) provides information on macroeconomic events often related to society or the environment, such as public health and policy (Brodeur et al , 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The outbreak of the pandemic has also affected the content internet users search on the internet and a significant surge reported in search terms related to COVID-19 (Pier et al , 2020). In the wake of COVID-19, many studies using Web-based data have been published using Google Trends (Mavragani and Gkillas, 2020; Riddell et al , 2022). The studies on the COVID-19 pandemic concerning Web search data are dichotomous.…”

Section: Introductionmentioning

confidence: 99%

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The COVID-19 pandemic and Google Search Trends

Alam,

Aziz,

Ansari

2024

JPMH

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Purpose This paper aims to investigate the association of COVID-19 confirmed cases and deaths with mental health, unemployment and financial markets-related search terms for the USA, the UK, India and worldwide using Google Trends. Design/methodology/approach The authors use Spearman’s rank correlation coefficients to assess the relationship between relative search volumes (RSVs) and mental health, unemployment and financial markets-related search terms, with the total confirmed COVID-19 cases as well as deaths in the USA, UK, India and worldwide. The sample period starts from the day 100 cases were reported for the first time, which is 7 March 2020, 13 March 2020, 23 March 2020 and 28 January 2020 for the US, the UK, India and worldwide, respectively, and ends on 25 June 2020. Findings The results indicate a significant increase in anxiety, depression and stress leading to sleeping disorders or insomnia, further deteriorating mental health. The RSVs of employment are negatively significant, implying that people are hesitant to search for new jobs due to being susceptible to exposure, imposed lockdown and social distancing measures and changing employment patterns. The RSVs for financial terms exhibit the varying associations of COVID-19 cases and deaths with the stock market, loans, rent, etc. Research limitations/implications This study has implications for the policymakers, health experts and the government. The state governments must provide proper medical facilities and holistic care to the affected population. It may be noted that the findings of this study only lead us to conclude about the relationship between COVID-19 cases and deaths and Google Trends searches, and do not as such indicate the effect on actual behaviour. Originality/value To the best of the authors’ knowledge, this is the first attempt to investigate the relationship between the number of COVID-19 cases and deaths in the USA, UK and India and at the global level and RSVs for mental health-related, job-related and financial keywords.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The COVID-19 pandemic and Google Search Trends

Alam,

Aziz,

Ansari

2024

JPMH

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Harnessing Google Health Trends Data for Epidemiologic Research

Neumann¹,

Mason²,

Farkas³

et al. 2022

American Journal of Epidemiology

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Interest in using internet search data, such as that from the Google Health Trends Application Programming Interface (GHT-API), to measure epidemiologically relevant exposures or health outcomes is growing due to their accessibility and timeliness. Researchers input search term(s), geography and time period, and the GHT-API returns a scaled probability of that search term, given all searches within the specified geo-time period. In this study, we detail a method for using these data to measure a construct of interest in five iterative steps: first, identify phrases the target population may use to search for the construct of interest; second, refine candidate search phrases with incognito Google searches to improve sensitivity and specificity; third, craft the GHT-API search term(s) by combining the refined phrases; fourth, test search volume and choose geographic and temporal scales; and fifth, retrieve and average multiple samples to stabilize estimates and address missingness. An optional sixth step involves accounting for changes in total search volume by normalizing. We present a case study examining weekly state-level child abuse searches in the United States during the COVID-19 pandemic (January 2018-August 2020) as an application of this method and describe limitations.

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US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic

Cited by 2 publications

References 30 publications

The COVID-19 pandemic and Google Search Trends

The COVID-19 pandemic and Google Search Trends

Harnessing Google Health Trends Data for Epidemiologic Research

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