Evidence map›Paper›PMID 32835202›Full record

ArticleGlobal transitions2020

Predictors of COVID-19 voluntary compliance behaviors: An international investigation.

Cory Clark, Andrés Davila, Maxime Regis, Sascha Kraus

Abstract read
In one paragraph

Article in Global transitions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 257 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
257citing papers in PubMed, 1 pooled it
–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

257 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Improving Hand Hygiene Behavior Using a Novel Theory-Based Intervention During the COVID-19 Pandemic.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2022
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  15. A survey of perceptions and behavioural responses towards the COVID-19 pandemic in South Africa.African journal of primary health care & family medicine · 2025
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197 more citing papers are in PubMed but not listed here.

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.

Cory ClarkHeterodox Academy, New York, USA.
Andrés DavilaESCE International Business School, INSEEC U Research Center & Praditus SAS, Paris, France.
Maxime RegisUniversité Panthéon Assas Paris II, LARGEPA & Praditus SAS, Paris, France.
Sascha KrausDurham University, Durham University Business School, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With a large international sample (n = 8317), the present study examined which beliefs and attitudes about COVID-19 predict 1) following government recommendations, 2) taking health precautions (including mask wearing, social distancing, handwashing, and staying at home), and 3) encouraging others to take health precautions. The results demonstrate the importance of believing that taking health precautions will be effective for avoiding COVID-19 and generally prioritizing one's health. These beliefs continued to be important predictors of health behaviors after controlling for demographic and personality variables. In contrast, we found that perceiving oneself as vulnerable to COVID-19, the perceived severity of catching COVID-19, and trust in government were of relatively little importance. We also found that women were somewhat more likely to engage in these health behaviors than men, but that age was generally unrelated to voluntary compliance behaviors. These findings may suggest avenues and dead ends for behavioral interventions during COVID-19 and beyond.

Indexed as

COVID-19Government trustHealth behaviorRule compliance

Identifiers

PMID32835202
PMCPMC7318969

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.