Evidence map›Paper›PMID 34081592›Full record

ArticleJMIR mental health2021

Mental Health and the Perceived Usability of Digital Mental Health Tools Among Essential Workers and People Unemployed Due to COVID-19: Cross-sectional Survey Study.

Felicia Mata-Greve, Morgan Johnson, Michael D Pullmann, Emily C Friedman, Isabell Griffith Fillipo, Katherine A Comtois, Patricia Arean

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

7 authors at 1 institution in 1 country.

Felicia Mata-GreveDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-6218-2917
Morgan JohnsonDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-2081-6176
Michael D PullmannDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0001-8404-864X
Emily C FriedmanDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-9520-0499
Isabell Griffith FillipoDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-6879-3268
Katherine A ComtoisDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0003-0398-4108
Patricia AreanDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0001-5971-6319
University of Washington · US

Funding

UW ALACRITY Center for Psychosocial Interventions ResearchP50MH115837 · NIMH · UNIVERSITY OF WASHINGTON · PI Michael David Pullmann · 2018 to 2026
$18.2M
Psychiatry Primary Care NRSA T-32 AwardT32MH020021 · NIMH · UNIVERSITY OF WASHINGTON · PI JOHN C. FORTNEY, JURGEN UNUTZER · 1998 to 2026
$5.6M
NIMH NIH HHS P50 MH115837NIMH NIH HHS T32 MH020021
6 · The paper itself

Abstract

backgroundCOVID-19 has created serious mental health consequences for essential workers or people who have become unemployed as a result of the pandemic. Digital mental health tools have the potential to address this problem in a timely and efficient manner.

objectiveThe purpose of this study was to document the extent of digital mental health tool (DMHT) use by essential workers and those unemployed due to COVID-19, including asking participants to rate the usability and user burden of the DMHT they used most to cope. We also explored which aspects and features of DMHTs were seen as necessary for managing stress during a pandemic by having participants design their own ideal DMHT.

methodsA total of 2000 people were recruited from an online research community (Prolific) to complete a one-time survey about mental health symptoms, DMHT use, and preferred digital mental health features.

resultsThe final sample included 1987 US residents that identified as either an essential worker or someone who was unemployed due to COVID-19. Almost three-quarters of the sample (1479/1987, 74.8%) reported clinically significant emotional distress. Only 14.2% (277/1957) of the sample used a DMHT to cope with stress associated with COVID-19. Of those who used DMHTs to cope with COVID-19, meditation apps were the most common (119/261, 45.6%). Usability was broadly in the acceptable range, although participants unemployed due to COVID-19 were less likely to report user burden with DMHTs than essential workers (t

conclusionsDespite the potential need for DMHTs, this study found that the use of such tools remains similar to prepandemic levels. This study also found that regardless of the level of distress or even past experience using an app to cope with COVID-19, it is possible to develop a COVID-19 coping app that would appeal to a majority of essential workers and unemployed persons.

Indexed as

COVID-19digital healthdistresse-mental healthessential workermental healthsurveyunemployedusabilityuser burden

Identifiers

PMID34081592
PMCPMC8354319
OpenAlexW3160535899

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.