Evidence map›Paper›PMID 36041005›Full record

ArticleJournal of medical Internet research2022

The Impact of the COVID-19 Pandemic on Internet Use and the Use of Digital Health Tools: Secondary Analysis of the 2020 Health Information National Trends Survey.

Billy Zeng, Natalie A Rivadeneira, Anita Wen, Urmimala Sarkar, Elaine C Khoong

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
12.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Pooled it
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  5. Observational
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  11. Patterns of Online Stress Management Information-Seeking Behavior in Hungary.International journal of environmental research and public health · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Billy ZengSchool of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0002-4653-3772
Natalie A RivadeneiraDivision of General Internal Medicine at Zuckerberg San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0003-2421-9915
Anita WenDepartment of Nutrition, University of California Davis, Davis, CA, United States.ORCID 0000-0002-9068-2978
Urmimala SarkarDivision of General Internal Medicine at Zuckerberg San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0003-4213-4405
Elaine C KhoongDivision of General Internal Medicine at Zuckerberg San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID 0000-0002-2514-3572
San Francisco General Hospital · USUniversity of California, Davis · USUniversity of California, San Francisco · US

Funding

Institutional Career Development Core SupplementKL2TR001870 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KANAYA, ALKA M., SARKAR, URMIMALA · 2016 to 2025
$19.7M
UCSF Career Development Program in Implementation Research in Heart and Lung DiseasesK12HL138046 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BIBBINS-DOMINGO, KIRSTEN, CATTAMANCHI, ADITHYA · 2017 to 2021
$2.9M
Designing a Remote Monitoring Intervention for Value & Equity in Hypertension (DRIVE-HTN)K23HL157750 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KHOONG, ELAINE · 2021 to 2025
$921k
Improving Survivorship Care for Diverse Cancer Patients Cared for in Safety-net SettingsK24CA212294 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SARKAR, URMIMALA · 2017 to 2021
$831k
NCATS NIH HHS KL2 TR001870NCI NIH HHS K24 CA212294NHLBI NIH HHS K12 HL138046NHLBI NIH HHS K23 HL157750
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic increased the use of digital tools in health care (eg, patient portal, telemedicine, and web-based scheduling). Studies have shown that older individuals, racial/ethnic minority groups, or populations with lower educational attainment or income have lower rates of using digital health tools. Digitalization of health care may exacerbate already existing access barriers in these populations.

objectiveThis study evaluated how use of digital tools to asynchronously communicate with clinicians, schedule appointments, and view medical records changed near the beginning of the pandemic.

methodsUsing 2020 Health Information National Trends Survey (HINTS) data, we examined internet use and 7 digital health technology use outcomes (electronic communication with a provider, electronic appointment scheduling, electronic test result viewing, patient portal access, portal use to download health records, portal use for patient-provider communication, and portal use to view test results). The HINTS surveyors designated surveys received after March 11, 2020, as postpandemic responses. Using weighted logistic regression, we investigated the impact of the pandemic after adjusting for sociodemographic traits (age, race/ethnicity, income, education, and gender), digital access (having ever used the internet and smartphone/tablet ownership), and health-related factors (insurance coverage, caregiver status, having a regular provider, and chronic diseases). To explore differences in changes in outcomes among key sociodemographic groups, we tested for significant interaction terms between the pandemic variable and race/ethnicity, age, income, and educational attainment.

resultsThere were 3865 respondents (1437 prepandemic and 2428 postpandemic). Of the 8 outcomes investigated, the pandemic was only significantly associated with higher odds (adjusted odds ratio 1.99, 95% CI 1.18-3.35) of using electronic communication with a provider. There were significant interactions between the pandemic variable and 2 key sociodemographic traits. Relative to the lowest income group (<US $20,000), the highest income group (≥US $75,000) had increased growth in the odds of ever having used the internet in postpandemic responses. Compared to the most educated group (postbaccalaureates), groups with lower educational attainment (high school graduates and bachelor's degree) had lower growth in the odds of using electronic communication with a provider in postpandemic responses. However, individuals with less than a high school degree had similar growth to the postbaccalaureate group in using electronic communication with a provider.

conclusionsOur study did not show a widespread increase in use of digital health tools or increase in disparities in using these tools among less advantaged populations in the early months of the COVID-19 pandemic. Although some advantaged populations reported a greater increase in using the internet or electronic communication with a provider, there were signs that some less advantaged populations also adapted to an increasingly digital health care ecosystem. Future studies are needed to see if these differences remain beyond the initial months of the pandemic.

Indexed as

COVID-19EcosystemEthnicityHumansInternetInternet UseMinority GroupsPandemicsSurveys and QuestionnairesCOVID-19digital divideeHealthtelehealth

Identifiers

PMID36041005
PMCPMC9488546
OpenAlexW4293585797

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.