Evidence map›Paper›PMID 36041237›Full record

ArticleSocial science & medicine (1982)2022

Determinants of voluntary compliance: COVID-19 mitigation.

Meng-Hao Li, Kingsley Haynes, Rajendra Kulkarni, Abu Bakkar Siddique

Abstract read
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 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

4 authors.

Meng-Hao LiSchar School of Policy and Government, George Mason University, Arlington, VA, 22201 USA.
Kingsley HaynesSchar School of Policy and Government, George Mason University, Arlington, VA, 22201 USA. Electronic address: khaynes@gmu.edu.
Rajendra KulkarniSchar School of Policy and Government, George Mason University, Arlington, VA, 22201 USA.
Abu Bakkar SiddiqueSchar School of Policy and Government, George Mason University, Arlington, VA, 22201 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the pre-vaccine period, the success of containing the spread of COVID-19 depends upon how communities respond to non-pharmaceutical mitigation policies such as social distancing, wearing of masks, retail and dining constraints, crowd limitation, and shelter-in-place orders. Of these policies, shelter-in-place and social distancing are of central importance. By using county-level mobility data as a measure of a community's voluntary compliance with social distancing policies, this study found that counties who received strong state social distancing policy directives and who had a high pro-social character showed lower mobility on retail and recreation mobility and grocery and pharmacy mobility (better social distancing) after states reopened from shelter-in-place orders. Counties that experienced a longer duration of shelter-in-place orders showed higher mobility (less social distancing), implying that the duration of the shelter-in-place order deteriorated social distancing response after reopening. This may be because reopening sent a "safe" signal to these counties or resulted in a response to the pent-up demand inducing higher mobility. The results indicate that implementing shelter-in-place and social distancing policies to slow down the transmission of COVID-19 were not necessarily effective in motivating a county to reduce mobility voluntarily. A county's pro-social character and the duration of shelter-in-place order should be considered when designing COVID-19 mitigation policies.

Indexed as

COVID-19HumansMasksPhysical DistancingUnited StatesCOVID-19MitigationPro-social characteristicsShelter-in-PlaceSocial distancing

Identifiers

PMID36041237
PMCPMC9404080

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.