Evidence map›Paper›PMID 35125233›Full record

ArticleSocial science & medicine (1982)2022

Commentary on "Different roles of interpersonal trust and institutional trust in COVID-19 pandemic control".

Anna Stefaniak, Michael J A Wohl, Frank J Elgar

Abstract readComment
In one paragraph

Article in Social science & medicine (1982), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Anna StefaniakDepartment of Psychology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada; Department of Psychology, Hebrew University of Jerusalem, Isreal. Electronic address: anna.stefaniak@carleton.ca.
Michael J A WohlDepartment of Psychology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada. Electronic address: michael.wohl@carleton.ca.
Frank J ElgarSchool of Population and Global Health, McGill University, 2001 McGill College Avenue, Montreal, Quebec, Canada. Electronic address: frank.elgar@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing number of epidemiologic studies have identified trust as a social determinant of COVID-19 mortality. Trust influences public compliance with policies aimed at containing the pandemic through physical distancing, wearing masks, and vaccine uptake. However, whilst some forms of trust are public assets (e.g., trust in government), others might be liabilities (e.g., trust in close friends and family members). Contributing to this body of work, Lou et al. (2022) examined associations of trust with COVID-19 fatality rates and willingness to get tested for COVID-19. Using correlation analyses, behavioral experiments, and agent-based modeling, they found institutional trust predicted lower COVID-19 fatality rates and greater willingness to get tested. In contrast, interpersonal trust predicted the speed with which COVID-19 was controlled in the early stages of the pandemic and people's willingness to obey norms preventing the spread of the virus (e.g., decreased nonessential outdoor activity). Investigations such as this offer useful knowledge to public health officials on ways to mitigate a pandemic. This commentary examines the pivotal role of social science in pandemic control, which up to now has been underfunded and overshadowed by the race to develop vaccines. We also highlight the importance of theory, particularly in research on trust, to producing evidence that is replicable and meaningful for policy application.

Indexed as

COVID-19PandemicsHumansMasksSARS-CoV-2Trust

Identifiers

PMID35125233
PMCPMC8806048

What OpenQuestion holds

Textmetadata
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.