Evidence map›Paper›PMID 35502405›Full record

ArticleJAMIA open2022

Assessing and addressing COVID-19 information needs via a weather application.

Mollie M McKillop, Courtney VanHouten, Carol Bales, Winnie Felix, Rezzan Hekmat, Gretchen Purcell Jackson

Abstract read
In one paragraph

Article in JAMIA open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Mollie M McKillopCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.
Courtney VanHoutenCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.
Carol BalesConsumer Insights, The Weather Company, Atlanta, Georgia, USA.
Winnie FelixCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.
Rezzan HekmatCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.
Gretchen Purcell JacksonCenter for AI Research and Evaluation, IBM Watson Health, Cambridge, Massachusetts, USA.ORCID https://orcid.org/0000-0002-3242-8058

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe implementation and usage of a coronavirus disease 2019 (COVID-19) digital information hub delivered through the widely adopted The Weather Company (TWC) application and explore COVID-19 knowledge, behaviors, and information needs of users. TWC deployed the tool, which displayed local case counts and trends, in March 2020. Unique users, visits, and interactions with tool features were measured. In August 2020, a cross-sectional survey assessed respondent characteristics, COVID-19 knowledge, behaviors, and preferences. TWC COVID-19 hub averaged 1.97 million unique users with over 2.6 million visits daily and an average interaction time of 1.63 min. Respondents reported being knowledgeable about COVID-19 (92.3%) and knowing relevant safety precautions (90.9%). However, an average of 35.3% of respondents reported not increasing preventive practices across behaviors surveyed due to information about COVID-19. In conclusion, we find a free weather application delivered COVID-19 data to millions of Americans. Despite confidence in knowledge and best practices for prevention, over one-third of survey respondents did not increase practice of preventive behaviors due to information about COVID-19.

Indexed as

consumer health informaticsconsumer health information needsCOVID-19public healthweather

Identifiers

PMID35502405
PMCPMC9037469

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.