Evidence map›Paper›PMID 36166436›Full record

ArticlePloS one2022

Willingness to share contacts in case of COVID-19 positivity-predictors of collaboration resistance in a nation-wide Italian survey.

Boris Bikbov, Mauro Tettamanti, Alexander Bikbov, Barbara D'Avanzo, Alessia Antonella Galbussera, Alessandro Nobili, Gemma Calamandrei, Valentina Candini, Fabrizio Starace, Cristina Zarbo and 1 more

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

Boris BikbovDipartimento di Politiche per la Salute, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.ORCID 0000-0002-1925-7506
Mauro TettamantiDipartimento di Politiche per la Salute, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Alexander BikbovCentre Maurice Halbwachs, École des hautes études en sciences socials, Paris, France.
Barbara D'AvanzoDipartimento di Politiche per la Salute, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Alessia Antonella GalbusseraDipartimento di Politiche per la Salute, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.ORCID 0000-0003-0163-1034
Alessandro NobiliDipartimento di Politiche per la Salute, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Gemma CalamandreiCentro di Riferimento per le Scienze Comportamentali e la Salute Mentale, Istituto Superiore di Sanita, Rome, Italy.
Valentina CandiniDipartimento di Salute Mentale, Azienda Unità Sanitaria Locale di Modena, Modena, Italy.
Fabrizio StaraceDipartimento di Salute Mentale, Azienda Unità Sanitaria Locale di Modena, Modena, Italy.
Cristina ZarboUnità di Psichiatria Epidemiologica a Valutativa, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Giovanni de GirolamoUnità di Psichiatria Epidemiologica a Valutativa, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.ORCID 0000-0002-1611-8324

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe unwillingness to share contacts is one of the least explored aspects of the COVID-19 pandemic. Here we report the factors associated with resistance to collaborate on contact tracing, based on the results of a nation-wide survey conducted in Italy in January-March 2021. METHODS AND

findingsThe repeated cross-sectional on-line survey was conducted among 7,513 respondents (mean age 45.7, 50.4% women) selected to represent the Italian adult population 18-70 years old. Two groups were defined based on the direct question response expressing (1) unwillingness or (2) willingness to share the names of individuals with whom respondents had contact. We selected 70% of participants (training data set) to produce several multivariable binomial generalized linear models and estimated the proportion of variation explained by the model by McFadden R2, and the model's discriminatory ability by the index of concordance. Then, we have validated the regression models using the remaining 30% of respondents (testing data set), and identified the best performing model by removing the variables based on their impact on the Akaike information criterion and then evaluating the model predictive accuracy. We also performed a sensitivity analysis using principal component analysis. Overall, 5.5% of the respondents indicated that in case of positive SARS-CoV-2 test they would not share contacts. Of note, this percentage varied from 0.8% to 46.5% depending on the answers to other survey questions. From the 139 questions included in the multivariable analysis, the initial model proposed 20 independent factors that were reduced to the 6 factors with only modest changes in the model performance. The 6-variables model demonstrated good performance in the training (c-index 0.85 and McFadden R2 criteria 0.25) and in the testing data set (93.3% accuracy, AUC 0.78, sensitivity 30.4% and specificity 97.4%). The most influential factors related to unwillingness to share contacts were the lack of intention to perform the test in case of contact with a COVID-19 positive individual (OR 5.60, 95% CI 4.14 to 7.58, in a fully adjusted multivariable analysis), disagreement that the government should be allowed to force people into self-isolation (OR 1.79, 95% CI 1.12 to 2.84), disagreement with the national vaccination schedule (OR 2.63, 95% CI 1.86 to 3.69), not following to the preventive anti-COVID measures (OR 3.23, 95% CI 1.85 to 5.59), the absence of people in the immediate social environment who have been infected with COVID-19 (1.66, 95% CI 1.24 to 2.21), as well as difficulties in finding or understanding the information about the infection or related recommendations. A limitation of this study is the under-representation of persons not participating in internet-based surveys and some vulnerable groups like homeless people, persons with disabilities or migrants.

conclusionsOur analysis revealed several groups that expressed unwillingness to collaborate on contact tracing. The identified patterns may play a principal role not only in the COVID-19 epidemic but also be important for possible future public health threats, and appropriate interventions for their correction should be developed and ready for the implementation.

Indexed as

COVID-19AdolescentAdultAgedContact TracingCross-Sectional StudiesFemaleHumansMaleMiddle AgedPandemicsSARS-CoV-2Young Adult

Identifiers

PMID36166436
PMCPMC9514658

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.