Literature DB >> 33822737

Rise in Use of Digital Mental Health Tools and Technologies in the United States During the COVID-19 Pandemic: Survey Study.

Dara H Sorkin1, Emily A Janio1, Elizabeth V Eikey2,3, Margaret Schneider4, Katelyn Davis5, Stephen M Schueller6,7, Nicole A Stadnick8,9,10, Kai Zheng7, Martha Neary6, David Safani11, Dana B Mukamel1.   

Abstract

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically.
OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health.
METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects.
RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types.
CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy. ©Dara H Sorkin, Emily A Janio, Elizabeth V Eikey, Margaret Schneider, Katelyn Davis, Stephen M Schueller, Nicole A Stadnick, Kai Zheng, Martha Neary, David Safani, Dana B Mukamel. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.04.2021.

Entities:  

Keywords:  COVID-19; MTurk; anxiety; depression; digital health; digital technologies; distress; e-mental health; mHealth; mental health; self-management

Year:  2021        PMID: 33822737     DOI: 10.2196/26994

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


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