Evidence map›Paper›PMID 34792469›Full record

ArticleJMIR formative research2021

Re-examining COVID-19 Self-Reported Symptom Tracking Programs in the United States: Updated Framework Synthesis.

Miranda Lynn Janvrin, Jessica Korona-Bailey, Tracey Pérez Koehlmoos

Abstract read
In one paragraph

Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Miranda Lynn Janvrin *The Henry M Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States.ORCID https://orcid.org/0000-0002-3083-5581
Jessica Korona-BaileyThe Henry M Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States.ORCID https://orcid.org/0000-0002-0314-5171
Tracey Pérez KoehlmoosUniformed Services University of the Health Sciences, Bethesda, MD, United States.ORCID https://orcid.org/0000-0003-1377-8615

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly in the pandemic, in 2020, Koehlmoos et al completed a framework synthesis of currently available self-reported symptom tracking programs for COVID-19. This framework described relevant programs, partners and affiliates, funding, responses, platform, and intended audience, among other considerations.

objectiveThis study seeks to update the existing framework with the aim of identifying developments in the landscape and highlighting how programs have adapted to changes in pandemic response.

methodsOur team developed a framework to collate information on current COVID-19 self-reported symptom tracking programs using the "best-fit" framework synthesis approach. All programs from the previous study were included to document changes. New programs were discovered using a Google search for target keywords. The time frame for the search for programs ranged from March 1, 2021, to May 6, 2021.

resultsWe screened 33 programs, of which 8 were included in our final framework synthesis. We identified multiple common data elements, including demographic information such as race, age, gender, and affiliation (all were associated with universities, medical schools, or schools of public health). Dissimilarities included questions regarding vaccination status, vaccine hesitancy, adherence to social distancing, COVID-19 testing, and mental health.

conclusionsAt this time, the future of self-reported symptom tracking for COVID-19 is unclear. Some sources have speculated that COVID-19 may become a yearly occurrence much like the flu, and if so, the data that these programs generate is still valuable. However, it is unclear whether the public will maintain the same level of interest in reporting their symptoms on a regular basis if the prevalence of COVID-19 becomes more common.

Indexed as

coronavirusCOVID-19digital healthframework analysisinformation resourcesmonitoringpatient-reported outcome measuresself-reportedsurveillancesymptom trackingsynthesis

Identifiers

PMID34792469
PMCPMC8651180

What OpenQuestion holds

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LicenceCC BY
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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.